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April 15 2019

Data Integration in the Cloud Era

Case Studies Tips and Tricks on How to Succeed

Based in Naples FL

Offers over 30 years of experience in infrastructure database and

data warehouse development in the Oracle applications analytics

and business intelligence (BI) areas

Held technical leadership and consulting leadership roles at

organizations including BearingPoint J amp H Marsh McLennan

Tektronix The Walt Disney Company and Western Digital

Holds a BS in Science Math and Technology from Empire State

College with a concentration in Artificial Intelligence and Machine

Learning

Most recently completed the Data Science Certification program at

the Harvard University Extension School

Awarded the 2018 ODTUG Women in Technology (WIT)

Scholarship for her contributions to the Oracle technology field

A frequent presenter at local and national Oracle events

A multi-year Women in Science and Engineering (WISE) mentor at

University of Central Florida

copy 2019 Performance Architects Inc Proprietary amp Confidential Page 2

Introductions Linda Stewart

Source Performance Architects

Linda Stewart

Manager amp Architect

lindastewartperformancearchitectscom

httpswwwlinkedincomin

linda-stewart-a41179150

Based in Boston MA

Maintains 20+ years of experience in the consulting internet

services and software markets

She is the Co-Chair of the Oracle Application Users Group

(OAUG) Oracle Analytics Business Intelligence and Big Data

Special Interest Group (SIG) participates in several OAUG

committees sits on the Boards of the BIWA User Community

Analytics and Data Summit and sits on the ODTUG BI Volunteer

Community Committee

Holds a BA from Yale University with Honors in Philosophy and

Political Science

Frequent presenter at industry events and writes for groups such

as Association for Financial Professionals

(AFP) BeyeNetwork ComputerWorld Enterprise Systems Higher

Education Data Warehousing Forum Information

Management The National Association of College and University

Business Officers (NACUBO) NICSA and The Data Warehousing

Institute (TDWI) as well as local and national Oracle events such

as Oracle OpenWorld Oracle Application Users Group (OAUG)

COLLABORATE and the Oracle Higher Education User Group

(HEUG) Alliance Conference


Introductions Kirby Lunger


Kirby Lunger

Partner

Chief Sales and Marketing Officer

+1 (617) 699-9354

kirbylungerperformancearchitectscom

httpswwwlinkedincominkirbylunger

Performance Architects Overview and Qualifications

Data Modeling and Data Management Definitions Concepts and

Vendor Landscape

The Data Integration Lifecycle

Data Integration Options On-Premises Public Cloud Hybrid

The Real World A Hybrid Data Integration Cloud Case Study

Questions and Special Offer


Document Outline


Overview amp Background

Facts and

Figures

Founded in 2006

Management

consulting and

systems integration

leader

Privately held with

solid growth and

profitability since

founding

Headquartered in

Boston MA

Operations across the

US and in India

Customer

Focus

Functional and

technical backgrounds

with practical and

relevant industry

experience

We love our work

enjoy teaching what we

know and have fun

doing our jobs

Familiar with all major

project methods and

use whatrsquos best for

your situation

The Team

Partnered with market

leaders across the

analyticsBI EPM and

supporting technology

markets

100 of staff certified

and trained in these

technologies

Deeply involved in

partner association

and technology

leadership groups

Partnerships

We are proud of our

100 client

reference-ability

Hundreds of clients

and solutions

95 repeat

business rate

Main focus is

enterprise analytics

(BIAnalytics and EPM)

within certain vertical

markets



Our Technical Expertise and Todayrsquos Conversation Focus

DatabasesNon-Relational Database (NoSQL) Relational Database (SQL)

Data ManagementData Management amp Integration

(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart

Operational Data Store

(ODS)

Data SourcesCRM HCM ERP

SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources

Business SolutionsStrategy

Management

Business or

Enterprise Analytics

Financial Management

Budgeting Forecasting amp Planning

Profitability amp Cost Management

Close amp Consolidation

Delivered on-premises hybrid or in the cloud via all relevant devices


Topics wersquore covering today


Representative Higher Education Clients




Vendor Landscape






Document Outline





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or









What is Data Management and Integration

Data integration involves combining data residing in

different sources to provide users with a unified view

of the data This process becomes significant in a

variety of situations which include both commercial

and scientific domains

copy 2019 Performance Architects Inc Proprietary amp Confidential 0Source Wikipedia

ETL versus ELT

ETL (Extract Transform Load) is normally a continuous ongoing

process with a well-defined workflowndash ETL first extracts data from data sources

ndash Typically the ETL is performed on an intermediate server

ndash Data is cleansed enriched transformed then stored either back in the data

lake or in a data warehouse

ELT (Extract Load Transform) is a variant of ETLndash The extracted data is loaded into the target system as the initial step

ndash Transformations are performed after the data is loaded into the data

warehouse

ndash ELT typically works well when the target database system is powerful enough

to handle transformations

copy 2019 Performance Architects Inc Proprietary amp Confidential Page 11Source Performance Architects

Why Do We Need Data Integration

Operational insights

Collaboration

Bridging gaps

Unifying data views

Faster answers to business questions

Better answers to business questions

Competitive edge

Itrsquos the glue that connects everything together


Gartner Magic Quadrant

Data Integration Tools (2018)

copy 2019 Performance Architects Inc Proprietary amp Confidential Page 13Source Gartner

The market for data integration tools includes vendors that offer software products to enable the construction

and implementation of data access and data delivery infrastructure for a variety of

data integration scenarios including

Support for governance and management of data assets

Data acquisition for analytics and business intelligence (BI) and

data warehousing

Sourcing and delivery of master data in support of

master data management (MDM)

Data consistency between operational applications

Interenterprise data sharing


Enterprise Platform Infrastructure as a Service (2018)


An iPaaS solution is typically used for cloud service integration (CSI)

application-to-application integration (A2A) business-to-business integration (B2B)

scenarios and increasingly for mobile application integration (MAI) and

IoT integration scenarios

Gartner considers an iPaaS solution to be enterprise iPaaS (EiPaaS) if it

Supports enterprise-class integration projects requiring high availabilitydisaster recovery

(HADR) security service-level agreements (SLAs) and technical support from the provider

Provides appropriate user experiences to the end user of the platform to allow the subscriber to

develop integration capabilities independent of the EiPaaS providers professional services

Can be used for multiple integration scenarios including application integration and

data integration use cases

Is fully managed by the vendor for patching and upgrades client-managed software components

are not considered to be part of an EiPaaS offering

Provides flexibility for the deployment of the runtime engine for a number of

hybrid deployment options


Metadata Management (2018)


Solutions are not all identical in scope or capability

Not all vendors offer all these capabilities and not all vendor solutions offer these capabilities in one product

bull Metadata repositoriesbull Business glossary bull Data lineagebull Impact analysisbull Rules management bull Semantic frameworks bull Metadata ingestion and translation

techniques including

Extraction transformation and loading (ETL) application integration data integration search

Business intelligence (BI) and reporting tools Modeling tools Database management system (DBMS)

catalogs ERP and other applications XML formats Hardware and network log files Microsoft Excel spreadsheetsWord documents PDF documents Business metadata Custom metadata





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or










Data Warehouses versus Data Lakes Academic Definitions

Source httpswwwkdnuggetscom201509data-lake-vs-data-warehouse-key-differenceshtml

Source kdnuggetscom

Data Warehouses versus Data Lakes How Integration Works


Data Warehouse versus Data Lake

Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics

Data Lakes Not Data Dumps

Source Performance Architects copy 2019 Performance Architects Inc Proprietary amp Confidential Page 19

A very expensive experiment or a strategic asset

Itrsquos your choice

PROS

Quickly move data to a

reporting instance

Possible to push data from

many sources

Useful for near real-time reports

Useful for exploration

CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security


Data Management Solutions for Analytics (DMSA) (2018)

Source Gartner copy 2019 Performance Architects Inc Proprietary amp Confidential Page 20

Gartner defines a data management

solution for analytics (DMSA) as a

complete software system that supports

and manages data in one or many file

management systems most commonly

a database or multiple databases

These management systems include

specific optimization strategies

designed for supporting analytical

processing mdash including but not limited

to relational processing nonrelational

processing (such as graph processing)

and machine learning or programming

languages such as Python or R

Data is not necessarily stored in a

relational structure and can use

multiple data models relational XML

JavaScript Object Notation (JSON)

key-value graph geospatial and others



Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure

bull Identify key sources ERP Campus Solutions

third party apps and cloud

bull Use JSON XML and web services

1

2

3

4

5

6

7

Explore

bull Includes ERD and source documentation

bull Understand data quality and semantics

bull Establish data standards

Cleanse

bull Identify and correct errors

bull Call out duplicates and outliers

bull Validate

Integrate

bull Identify relationships

bull Document source structure

bull Finalize deliverables

Deliver

bull Identify sensitive data

bull Ensure compliance security data privacy

encryption availability and refresh needs

Develop

bull Build the mappingdata integration code

bull Validate quality and assumptions

bull Ensure performance reliability and scalability

Manage

bull Audit and control paths

bull Manage operations

bull Tune as needed




Vendor Landscape






Document Outline

Data Integration Options On-Premises


On-Premises Public Cloud Hybrid Cloud

bull Utilize existing assets

bull General LedgerERP

bull Student Information

bull ETLELT

bull On-premises data

warehouse

bull On-premises data lake

bull Driven from source

system to target data

warehouse

bull Unlimited customizations

bull Secure

bull High reliability

bull Startup operations

bull Focus on product over IT

operations

bull Scalable on demand

bull Managed service

bull ldquoPay as you gordquo

bull Costs may escalate due to

bandwidth and storage

bull Few customizations

bull Less secure

bull Medium reliability

bull ldquoBest of breedrdquo approach

bull High flexibility

bull Scalable

bull Combination of private

and public cloud

bull Cost optimized solution

bull More secure than public

cloud

bull Medium to high reliability

Begin Process to Migrate

to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


A Typical On-Premises Data Integration Architecture


ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP


On-Premises Data Integration Architecture Next Steps


ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics


Data Integration Options Public Cloud






bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


A Typical Public Cloud Data Integration Architecture


ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics


Public Cloud Data Integration Architecture

Multi-Vendor Recommendations

Public cloud environments are typically highly complex with multiple

vendors at each layer of the stackndash Analytics Cognos OACOBIEE Power BI Qlik Tableau etc

ndash Data management and integration DataStage Informatica ODI SnapLogic

etc

ndash Data modeling and storage Amazon Redshift Microsoft Azure Oracle DB

Snowflake etc

The goal is to achieve one source of data for many versions of the

truth

There isnrsquot a great answerhellipthe easiest solution ishellipndash Standardize on one or more solutions at each layer of the stack especially

data integration and management

ndash Make sure you have a data governance process (aka make sure you know

what your data means even if there are multiple ways itrsquos defined)


Public Cloud Data Integration Architecture Next Steps

Monitor service level

Monitor costs

Secure your systems

Apply application and database patches

Ensure databases are backed up

Ensure database backups can be restored

Ensure your data can be moved off the cloud solution

Contractually ensure you can move your data off the public cloud at

any time


Data Integration Options Hybrid Cloud






bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems

Hybrid Cloud Data Integration Architecture

OACBICS Target

copy 2019 Performance Architects Inc Proprietary amp Confidential Page 34Source Oracle Corporation


Amazon Redshift Target

copy 2019 Performance Architects Inc Proprietary amp Confidential Page 35Source Informatica

Hybrid Cloud Data Integration Architecture Next Steps

Continue to analyze ldquobest in breedrdquo offerings

Monitor and continue to optimize the product and service mix

Verify service level agreements are met

Monitor costs

Adjust the cloud roadmap annually as the market is changing rapidly




Vendor Landscape






Document Outline


Source Dragnet -) copy 2019 Performance Architects Inc Proprietary amp Confidential Page 38

What is Oracle Analytics Cloud (OAC)

A scalable and secure public cloud service that provides a full set of capabilities to explore and perform collaborative analytics for you your workgroup and your enterprise

Provides flexible service management capabilities including fast setup easy scaling and patching and automated lifecycle management


OAC Features

Built on a high-performance platform with flexible data storage OAC provides a complete solution for deriving and sharing data insights

ndash Data preparation Analysts can ingest profile and cleanse data using a variety of algorithms

ndash Data flow Analysts can prepare transform and aggregate data and then run machine-learning models at scale

ndash Data discovery Subject matter experts can easily collaborate with other business users blending intelligent analysis at scale machine learning and statistical modeling

ndash Data visualization Analysts can visualize any data on any device on-premises and in the cloud

ndash Data collaboration Large organizations and small teams can share data more simply without the need to manage or consolidate multiple versions of spreadsheets and quickly perform ad hoc analysis of the spreadsheet data

ndash Data-driven Application developers can utilize interfaces that enable them to extend customize and embed rich analytic experiences in the application flow


Case Study A Large Public Research University


Reliable university-wide data is necessary to be successful

University strategic plan goals by

2024

ndash First year retention of 90

ndash Six-year graduation rate of 70

Data needed to predict outcomes

ndash Who is an active student

ndash What are the early warning signs a

student may be off track

ndash Do counseling scholarships and

money management contribute to

student success

Case Study Hybrid Migration Process (OBIEE to OAC)

The transition to the cloud can be accomplished through an incremental hybrid approach

For example this client followed three phases

1 Phase 1 bull Moved OBIEE on-premises platform environment to

OACbull Used Oracle Remote Data Connector to access on-

premises data warehouse and other sourcesbull Leveraged migration tools to move existing OBIEE

metadata and webcatalog to the cloud

2 Phase 2bull Migrated the data warehouse to Oracle DBCSbull Integrated data feeds from Financials and Campus

Solutions

3 Phase 31 Migrated Oracle Data Integrator (ODI) ELT processing

to a cloud-based platform


Case Study BI Pilot ndash Planning the Objectives

The pilot implementation of Oraclersquos OAC

service enabled the client to test the

migration of the on-premises OBIEE

environment to the OAC cloud

Identified and addressed potential issues

related to upgrading the OBIEE version from

11g to 12c as well as establishing a hybrid

cloud model that accesses data remaining

on-premises

Demonstrated the new features of OBIEE

12c in the cloud and OAC Data Visualization

capabilities


Case Study OAC Pilot Benefits

Demonstrate PaaS advantages related to hardware costs patching

upgrades and system maintenance

Low impact upgrade from OBIEE 11g on-premise to OBIEE 12c in the

cloud allowing for all new features of 12c to be available

Identify potential challenges with full transition to Oracle Cloud for all

on-premises OBIEE content

Oracle Data Visualization availability for users ready to explore more

advanced self-service analytics

Future expanded reporting capabilities from SaaS data sources like

HCM Cloud and Financials Cloud using OTBI as gateway


Case Study OAC Pilot ndash Risks to Manage

Connectivity to on-premises data warehouse may face challenges due

to network policies and Remote Data Connector configuration

Query performance across the network may not match current on-

premises environment performance

Configuration of current OBIEE security model using EBS for

establishing data access roles may require additional steps

Possible inconsistencies in dashboards analyses after upgrade to

OBIEE 12c in OAC


Case Study Outcomes

Successfully migrated OBIEE to the Oracle Analytics Cloud (OAC)

Defined ldquoactive studentrdquo

Provided a unified view of the student in OAC

Created an analytic view of student retention in the first year

Identified measures to predict graduation

Defined early warning signs for a ldquoat-risk studentrdquo

Constructed key metrics to identify ldquoat-riskrdquo students collected

Student success road map


In Summary Data Integration in the Cloud Era

Develop a longer-term road map especially an overall strategy and requirements for data integration

Evaluate current tools against strategy and requirements

Reduce complexity fewer vendors

Consider data masking and encryption

What needs to remain on-premises eg sensitive or regulated data

Determine what strategic activities the cloud offersndash Fast time to deployndash Easier upgradesndash Cheaper storage ndash Better storage technologiesndash Managed servicesndash Contain expenses

Patch Your Environments




Vendor Landscape






Document Outline


httpsperformancearchitectscomHEDW-2019-offer


Check Out Our Offer ndash Free Stuff

Curious to see if this data integration and governance data modeling and storage enterprise analytics BI big data data visualization neural networking and spatial and graph stuff actually works in the real world either on-premises in the cloud or in a hybrid environment

We understand

Performance Architects is offering all HEDW 2019 conference attendees either a free proof-of-concept (POC) using your organizationrsquos data and information or four free hours of consulting

Just fill in the form at the URL above and wersquoll be in touch to schedule

Offer does not apply to software vendor student or consulting company employees

To be eligible you must respond using this form by Monday May 27th A response to this offer does not obligate Performance Architects to

provide services (we need to see what we can reasonably accomplish with you during a POCfree consulting effort first)

Questions

Todayrsquos Presenters


Keep in Touch with Performance Architects

Bloghttpblogperformancearchitectscom

Twitter PerfArchitects

LinkedInhttpswwwlinkedincomcompany

performance-architects-inc-

Facebookhttpwwwfacebookcom

PerformanceArchitects

Learning Center (for archived webinar and

presentation materials)httpsperformancearchitectscom

learning-centers

YouTube HowTo Channelhttpwwwyoutubecomuser

PerformanceArchHowTo

Kirby Lungerkirbylungerperformancearchitectscom

Linda Stewartlindastewartperformancearchitectscom

Based in Naples FL

Offers over 30 years of experience in infrastructure database and

data warehouse development in the Oracle applications analytics

and business intelligence (BI) areas

Held technical leadership and consulting leadership roles at

organizations including BearingPoint J amp H Marsh McLennan

Tektronix The Walt Disney Company and Western Digital

Holds a BS in Science Math and Technology from Empire State

College with a concentration in Artificial Intelligence and Machine

Learning

Most recently completed the Data Science Certification program at

the Harvard University Extension School

Awarded the 2018 ODTUG Women in Technology (WIT)

Scholarship for her contributions to the Oracle technology field

A frequent presenter at local and national Oracle events

A multi-year Women in Science and Engineering (WISE) mentor at

University of Central Florida

copy 2019 Performance Architects Inc Proprietary amp Confidential

Introductions Linda Stewart


Linda Stewart

Manager amp Architect

lindastewartperformancearchitectscom

httpswwwlinkedincomin

linda-stewart-a41179150

Based in Boston MA








Community Committee


Political Science














Kirby Lunger

Partner


+1 (617) 699-9354





Vendor Landscape






Document Outline



Facts and

Figures

Founded in 2006

Management

consulting and

systems integration

leader

Privately held with

solid growth and

profitability since

founding

Headquartered in

Boston MA


US and in India

Customer

Focus

Functional and


with practical and

relevant industry

experience

We love our work


know and have fun

doing our jobs


project methods and


your situation

The Team


leaders across the

analyticsBI EPM and


markets



technologies

Deeply involved in

partner association

and technology

leadership groups

Partnerships

We are proud of our

100 client

reference-ability

Hundreds of clients

and solutions

95 repeat

business rate

Main focus is




markets






(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or














Vendor Landscape






Document Outline





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or















copy 2019 Performance Architects Inc Proprietary amp Confidential Page 10Source Wikipedia

ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers





Based in Boston MA








Community Committee


Political Science














Kirby Lunger

Partner


+1 (617) 699-9354





Vendor Landscape






Document Outline



Facts and

Figures

Founded in 2006

Management

consulting and

systems integration

leader

Privately held with

solid growth and

profitability since

founding

Headquartered in

Boston MA


US and in India

Customer

Focus

Functional and


with practical and

relevant industry

experience

We love our work


know and have fun

doing our jobs


project methods and


your situation

The Team


leaders across the

analyticsBI EPM and


markets



technologies

Deeply involved in

partner association

and technology

leadership groups

Partnerships

We are proud of our

100 client

reference-ability

Hundreds of clients

and solutions

95 repeat

business rate

Main focus is




markets






(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or














Vendor Landscape






Document Outline





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or
















ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers







Vendor Landscape






Document Outline



Facts and

Figures

Founded in 2006

Management

consulting and

systems integration

leader

Privately held with

solid growth and

profitability since

founding

Headquartered in

Boston MA


US and in India

Customer

Focus

Functional and


with practical and

relevant industry

experience

We love our work


know and have fun

doing our jobs


project methods and


your situation

The Team


leaders across the

analyticsBI EPM and


markets



technologies

Deeply involved in

partner association

and technology

leadership groups

Partnerships

We are proud of our

100 client

reference-ability

Hundreds of clients

and solutions

95 repeat

business rate

Main focus is




markets






(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or














Vendor Landscape






Document Outline





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or
















ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers







Facts and

Figures

Founded in 2006

Management

consulting and

systems integration

leader

Privately held with

solid growth and

profitability since

founding

Headquartered in

Boston MA


US and in India

Customer

Focus

Functional and


with practical and

relevant industry

experience

We love our work


know and have fun

doing our jobs


project methods and


your situation

The Team


leaders across the

analyticsBI EPM and


markets



technologies

Deeply involved in

partner association

and technology

leadership groups

Partnerships

We are proud of our

100 client

reference-ability

Hundreds of clients

and solutions

95 repeat

business rate

Main focus is




markets






(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or














Vendor Landscape






Document Outline





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or
















ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers









(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or














Vendor Landscape






Document Outline





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or
















ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers










Vendor Landscape






Document Outline





(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or
















ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers









(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or
















ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers











copy 2019 Performance Architects Inc Proprietary amp Confidential Source Wikipedia

ETL versus ELT








warehouse






Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers





ETL versus ELT








warehouse



copy 2019 Performance Architects Inc Proprietary amp Confidential Source Performance Architects



Collaboration

Bridging gaps

Unifying data views



Competitive edge











data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


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Continue Best Fit

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Patch your systems




ELT

Cloud Data

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Cloud

Student Information

General LedgerERP

Cloud

Analytics







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Monitor costs

Secure your systems






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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


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Monitor costs





Vendor Landscape






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OAC Features













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Vendor Landscape






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learning-centers







Collaboration

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(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


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SCM Systems

Legacy

Systems

Other Operational

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External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

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Data must be

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Raw data is

loaded to the

data lake

Data is cleansed

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Analytics





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many sources



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Sustainability

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Data catalogue

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Analyze

Design

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Student

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Student

Success




1

34

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6

7

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Integrate

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Develop

Determine

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Understand the

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1

2

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Document Outline







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warehouse


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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

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Data

Lake

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ELT

Cloud Data

Warehouse

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Data

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Student Information

General LedgerERP

Analytics

Cloud

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Analytics








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Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

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Cloud

Student Information

General LedgerERP

Cloud

Analytics







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Monitor costs

Secure your systems






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and public cloud



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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



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Vendor Landscape






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learning-centers







copy 2019 Performance Architects Inc Proprietary amp Confidential Source Gartner






data warehousing





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

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into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


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reporting instance


many sources



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Sustainability

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Data catalogue

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Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

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Develop

Determine

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access and

share data

Secure

Understand the

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Identify and

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Create

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Explore

Solutions

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1

2

3

4

5

6

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Deliver




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Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


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operations







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bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

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Data

Lake

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Cloud Data

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General LedgerERP

Analytics

Cloud

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Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


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Monitor costs

Secure your systems






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bull ETLELT


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and public cloud



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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



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Vendor Landscape






Document Outline






We understand






Questions












learning-centers





































(ETL ELT)

Data ModelingData

Lake

Data Warehouse

Data Mart


(ODS)


SCM Systems

Legacy

Systems

Other Operational

Systems

External Data

Sources


Management

Business or












Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






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Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

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implement

processes

Define how

data is

delivered

Create

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Monitor audit

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Explore

Solutions

and

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Secure




1

2

3

4

5

6

7

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Integrate




Deliver




Develop




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Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

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Data

Lake

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ELT

Cloud Data

Warehouse

Data Lake

Data

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Student Information

General LedgerERP

Analytics

Cloud

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Analytics








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Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

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Cloud

Student Information

General LedgerERP

Cloud

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Monitor costs

Secure your systems






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bull ETLELT


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operations







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and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers








Source kdnuggetscom




Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

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Define how

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Create

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and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



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Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

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Data

Lake

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ELT

Cloud Data

Warehouse

Data Lake

Data

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Student Information

General LedgerERP

Analytics

Cloud

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bull ETLELT


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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


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Monitor costs

Secure your systems






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bull ETLELT


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operations







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and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers








Data Integration

Data is extracted

and organized

into subject areas

Data must be

organized for

analytical value

Raw data is

loaded to the

data lake

Data is cleansed

and ready for

analytics


Analytics





PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

Warehouse

Data

Lake

Analytics




ELT

Cloud Data

Warehouse

Data Lake

Data

Warehouse

Student Information

General LedgerERP

Analytics

Cloud

Analytics

Analytics








bull ETLELT


warehouse




warehouse


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operations







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and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers






Source Performance Architects copy 2019 Performance Architects Inc Proprietary amp Confidential



PROS


reporting instance


many sources



CONS

Sustainability

Data governance

Data catalogue

Data quality

Data security

























Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

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Data

Lake

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ELT

Cloud Data

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Data Lake

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Student Information

General LedgerERP

Analytics

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Analytics

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bull ETLELT


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and public cloud



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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


truth








Monitor costs

Secure your systems






any time








bull ETLELT


warehouse




warehouse


bull Secure




operations







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and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers







Source Gartner copy 2019 Performance Architects Inc Proprietary amp Confidential






















Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

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Cloud Data

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General LedgerERP

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and public cloud



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Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


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Monitor costs

Secure your systems






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bull ETLELT


warehouse




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and public cloud



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to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









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Solutions













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Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






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Vendor Landscape






Document Outline



Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

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and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




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bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

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Data

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ELT

Cloud Data

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General LedgerERP

Analytics

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bull ETLELT


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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


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Monitor costs

Secure your systems






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bull ETLELT


warehouse




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bull Secure




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bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



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OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers







Transfer

Analyze

Design

Implement

Operate

Student

Advisor

Student

Success




1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

Secure

Understand the

data set

Identify and

clean errors

and

omissionsMap and

implement

processes

Define how

data is

delivered

Create

sustainable and

scalable code

and rules

Monitor audit

and tune

Explore

Solutions

and

Processes 2

Secure




1

2

3

4

5

6

7

Explore




Cleanse



bull Validate

Integrate




Deliver




Develop




Manage



bull Tune as needed




Vendor Landscape






Document Outline







bull ETLELT


warehouse




warehouse


bull Secure




operations







bull Less secure




bull Scalable


and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ETL

ELT

Data

Warehouse

Data

Warehouse

Analytics

Analytics

Student Information

General LedgerERP

Student Information

General LedgerERP




ELT

Student Information

General LedgerERP

Data

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Data

Lake

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ELT

Cloud Data

Warehouse

Data Lake

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Warehouse

Student Information

General LedgerERP

Analytics

Cloud

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bull ETLELT


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and public cloud



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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems




ELT

Cloud Data

Warehouse

Data Lake

Cloud

Student Information

General LedgerERP

Cloud

Analytics







etc


Snowflake etc


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Monitor costs

Secure your systems






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bull ETLELT


warehouse




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and public cloud



cloud



to the Cloud

Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

Patch your systems


OACBICS Target









Monitor costs





Vendor Landscape






Document Outline







OAC Features













2024









student success









Solutions













on-premises



capabilities






















OBIEE 12c in OAC


Case Study Outcomes





















Vendor Landscape






Document Outline






We understand






Questions












learning-centers







1

34

5

6

7

Manage

Cleanse

Integrate

Deliver

Develop

Determine

how to

access and

share data

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1

2

3

4

5

6

7

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Integrate




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Document Outline







bull ETLELT


warehouse




warehouse


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operations







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Monitor and Manage

Risk Factors

Continue Best Fit

Evolution

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ETL

ELT

Data

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Data

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Student Information

General LedgerERP

Student Information

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copy 2019 Performance Architects Inc Proprietary amp Confidential Source Oracle Corporation








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