analytics innovation, disruption, and transformation
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© 2016 SAP SE or an SAP affiliate company. All rights reserved. 1Internal
Analytics Innovation, Disruption,And TransformationSID 5978Timo Elliott, SAP
Use this title slide only with an image
Timo Elliott, SAP, October, 2016
Analytics Innovation, DisruptionAnd Transformation
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Agenda
Top Trends
Supporting “Modern BI”
Big Data Architectures
Organizing for Data
Conclusion
Top Trends
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Technology Priorities for 2016 and beyond
Rank Technology Trend
1 BI/Analytics2 Cloud3 Mobile4 Digitalization / Digital Marketing5 Infrastructure & Data Center6 ERP7 Security8 Industry-Specific Applications9 Customer Relationships
10 Networking, Voice, and Data Comms
Nine out ofeleven years2006-2016
ANALYTICS
#1
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 7Internal
By 2020, information will be used to
reinvent, digitalize, or
eliminate 80%of business processes and products
from a decade earlier.
From The Back Office To The Business Models of Future
”
“
@timoelliott
Live Business
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 9Internal
BI Success …
“BI initiatives described as ‘successful’ dropped from 41% to 35% in 2015”
Techtarget, 2015
Source: TechTaget
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BI is Dead!?…
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Are you a BI-nosaur?
© 2014 SAP AG. All rights reserved. 12
Complaints…
31% wait days or weeks for an average BI request
32% say Enterprise BI too complex, complicated, cumbersome to use
Enterprise systems don’t have all the data needed -- >45% from outside
Source: Forrester
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The Penetration of BI Remains Low
“Close to 40% of organizations report fewer than 10% of employees using BI”
Techtarget, 2015
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 14Internal
Supporting “Modern BI”
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 16Internal
Data-Driven Approach
Push:• From IT• Data-Driven• Data to Insight• Technology-Centric
A.S.P.I.R.E.
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Value-Driven Approach
Pull:• From LOB• Outcome-Driven• Insight to Data• Use-Case-Centric
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 18Internal
Combination Approach
Push:• From IT• Data-Driven• Data to Insight• Technology-Centric
Pull:• From LOB• Outcome-Driven• Insight to Data• Use-Case-Centric
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 19Internal
“Modern BI”
DATA Self-servicedata preparation
Structured/Unstructured
Internal/External
Batch/Streaming
Integration, blending
Cleansing, augmentation
Agile modeling
BI DBColumnar
In-memory
Self-servicedata analysis
Data discovery
Visual exploration
Dashboards/storytelling
Agile Iteration
OptionalData warehouse
Semantic layers
OLAP Cubes
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 20Internal
“Systems of Insight”
“Earlier-Generation BI Is No Longer Enough”
• Earlier-generation BI can’t keep up in the age of the customer.
• Agile BI and big data are the building blocks of systems of insight
Source: Forrester Research, Inc.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 21Internal
Pret A Manger
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 22Internal
© 2014 SAP AG. All rights reserved. 23
What Food to Make, When?
Knowledge
Check Past Sales
Check Forecast
Check Must Stock
Run and Check Range
Tool
Set 60%/70% Fixed First Production
Hot Food Continuous
Replenishment
All Other Food Monitor for 2nd
and 3rd Variable
Productions
© 2014 SAP AG. All rights reserved. 24
What Food to Make, When?
Trading Patterns
Core Range
Weather
Special Events
© 2014 SAP AG. All rights reserved. 25
Internal Data
External Data
Slow and Steady DataTransactional,
Changeable Data
POS Data
Deliveries
Store Attributes
Store Org Structure
Store Placement
Store Staff
Store Visibility, Signage
Competitor Store Attributes
Census, ONS Data
POI Data
GIS Competitor and Cannibalisation
Footfall
Weather
Events
Real Estate
Choosing a New Store Location
• $4.48 billion revenue• 40K employees• > 8M patients/year
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 27Internal
Mercy Health
Mercy — one of US Most Wired for 12th Year in a row!
“It is mind-blowing how versatile and nimble our data warehouse is on SAP HANA.”
Agile self-service with SAP HANA and SAP Lumira. 9 years of data, structured & unstructured
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 31Internal
Invest in Self-Service Data Discovery Tools
“Through 2020 spending on self-service visual discovery and data preparation market will grow 2.5x faster than traditional IT-controlled tools for similar functionality”
– IDC, 2015
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 32Internal
Invest in Self-Service Data Preparation
SAP Agile Data Preparation
I.e., “Data Blending” — combine, merge, cleanse data
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 33Internal
Invest in Predictive Analytics
Model deployed using In-Database-Apply
Customer Database
Hancock, John M 38 D Y 4.2 N Y
Doe, Jane F 45 M Y 9.4 N N
Red, Simply F 18 S N 2.1 N Y
SQL Dataset w/ Scoring
Business Users can get on-the-fly scoring without even knowing they are using predictive algorithms
BI Artifact(or even just a dataset)
SAP BI (3.x/4.x)
Embedded into any application
SQL
(Or any other application)
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 34Internal
SAP BusinessObjects Cloud
Big Data Architectures
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Big Data Architectures = Digital Business
By 2018, 40% of enterprise architecture teams teams will be distinguished as leaders by their primary focus on applying disruptive technologies to drive business innovation.
By 2018, 40% of enterprise architecture teams will be responsible for advancing the organization's digital business strategy.
By 2018, the new economics of connections will drive organizations to increase investments in connected physical assets and systems by 30%.
By 2018, 20% of enterprise architects will use business ecosystem modeling to identify and predict business moments.
By 2017, 20% of EA will be responsible for identifying new business designs that leverage business algorithms.
Source: Gartner, Predicts 2016: Five Key Trends Driving Enterprise Architecture Into the Future
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 37Internal
You Need Both of These…
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A Common Question
“We like SAP ERP (and HANA), we like Hadoop, and your BI tools are a standard. But we don’t understand how it’s all going to fit together. Help!”
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 39Internal
What is Hadoop?
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“Classic” Hadoop Use Cases
Semi-structured data loading / processing• First web data, now IoT / documents / images, etc.
Offload traditional relational DW• Typically no reduction in existing DW, but new data increasingly tiered
Queryable alternative to tape backups• E.g. when upgrade to different ERP system, keep copy of all old data
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 41Internal
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 42Internal
Coca-Cola East Japan Architecture
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Other Interesting Hadoop Use Cases
Fast scale up / down• Game apps company: big fan of Teradata, and found it cheaper to run than Hadoop, but when
individual games became a hit, they needed to be able to scale up (and down) fast
Avoid “brittle” ETL, push schema creation to the business• Large investment bank had dozens of different CRM setups, thousands of ETL jobs that kept
breaking – kept traditional DW, but added data lake -- “it’s all in there – have fun!”
Excel on steroids / exploration• Big, one-off decisions• We don’t know what we don’t know
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 44Internal
Sandboxing / Data Extensions
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Not Just a Data Store – A Platform
Far more than a batch-driven data store• Many still have an out of date view – Yarn / Spark etc• ”Data at Rest and Data in Motion”• But still not for “transactions” any time soon
Still maturing, still a lot of work, but has proved enterprise value• In particular, overcame biggest security & auditing concerns – Kerberos integration, encryption,
tokenization, Apache Ranger… • Low capital costs to try things out (but don’t underestimate time / training / expertise needed)
Considered the heart of “digital transformation” in some large organizations…• ...At least by the team implementing Hadoop! (but there’s typically a large ”traditional IT”
modernization effort going on at the same time)
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 46Internal
Centrica (British Gas)
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 47Internal
Zurich Insurance
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Some Projects
Atlas – open data governance
Ranger – policies and security
Nifi – data in motion
Flink – streaming data analytics
Zeppelin – analytic “notebooks”
Juypter, Kafka, Flume, Sqoop, etc etc
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 49Internal
Result of All This: Data Complexity For The Foreseeable Future
Data Warehouse
Hybrid Transaction/
Analytical Processing
Hadoop,MongoDB,Spark, etc Personal
Data / BI
Where does data arrive?When does it need to move?Where does modeling happen?What can users do themselves?What governance is required?
Big Data Architectures got complicated
What we would like — consistent, seamless solution
Data
Feeds
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 50Internal
SAP HANA VoraWhat’s Inside and What Does It Do?
DemocratizeData Access
Make PrecisionDecisions
SimplifyBig DataOwnership
SAP HANA Vora is an in-memory query engine which leverages and extends the Apache Spark execution framework to provide enriched interactive analytics on Hadoop. Drill Downs on HDFS
Mashup API EnhancementsCompiled Queries
HANA-Spark AdapterUnified LandscapeOpen Programming
Any Hadoop Clusters
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 51Internal
SAP Big Data Platform – “Hadoop Inside”Vision
HANA native BigData Dynamic Tiering Smart Data Streaming NoSQL | Graph | Geo |
TimeSeries
HANA & Hadoop SDA Hive | Spark MapReduce | HDFS Admin & Monitoring User Mgmt / Security
Hadoop Extension Vora Engine Integrated with HANA and
Hadoop
HANA Data Management Platform
Instant Results
SAP HANAIn-Memory
0.0sec ∞Infinite Storage Raw Data
HADOOPVora
Information Management | Text | Search | Graph | Geospatial | Predictive
Smart Data Streaming
Administration | Monitoring | Operations | User Management | Security
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 52Internal
Key Features -- Vora SQL Engine
#FEA433
Components
Written FromScratch
Multi Platform
Compressed Columns
Parallel QueryProcessing
In Memory Storage Fast Column Scans
Cache EfficientAlgorithms
Code Generation
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 53Internal
SAP HANA Vora Modeler
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 54Internal
SQL/OLAP on Big Data
• Hierarchical data storage of contextual data supports structured analysis
• Fast drill-down interaction aids in root-cause analysis
• Familiar OLAP tool enables experienced business analysts derive useful insights from contextual data
• Support for HDFS, Parquet and ORC formats
• LLVM/Clang – JIT compilation of query plans and execution
Hadoop/NoSQL DATA
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 55Internal
SQL-on-Hadoop using Vora
A different context allows access to SAP HANA data from Spark SQL
Creates an in-memory data object, similar to a Spark dataframe
Load data from HDFS, temp table will be distributed across Hadoop cluster
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 56Internal
SAP Predictive Analytics 3.0
Native Spark Modeling
Standalone or included in SAP HANA
Predictive Factory
Integration with cloud & other apps
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 57Internal
DW Directions
SAP HANA DW SAP HANA DWSAP HANA DWOptional Components
DW Foundation
PowerDesigner
HANA EIM
Business Warehouse
SAP HANA Platform
Planning and Definition2015
Market presence in Data Warehousing with a clear roadmap
Strong and simplified offering with tight integration
Convergence into one technology stack addressing BW and SQL-based
DW needs
DWH Foundation
PowerDesigner
HANA EIM
Business Warehouse
SAP HANA Platform
DW Modeling DW ETL & DM
SAP HANA Platform
Analytics , BI Suite, Predictive Analytics , BI Suite, Predictive Analytics , BI Suite, Predictive
HadoopSAP HANA Vora
HadoopSAP HANA Vora
HadoopSAP HANA Vora
This is the current state of planning and may be changed by SAP at any time.
Execution and Delivery2016-2018 Vision
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 58Internal
SAP HANA DW – Future-proof data management platform
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 59Internal
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 60Internal
Looking Forward to the Future: “Data Refineries”
Nobody believes that a single big data warehouse is THE solution any more• But they’re not going away any time soon • “Data warehouses are dead! Long live data warehousing!”
Instead:
Enterprise Information Catalog – transparency• Search for data: origin, owner, trust level, sensitivity, formats, how to order…
Data Factories – workflows, not just data• The collective know-how on getting, refining, displaying data
More info from Mike Ferguson, here:http://www.slideshare.net/HadoopSummit/organising-the-data-lake-information-management-in-a-big-data-world
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 61Internal
The Big Big Picture
Embrace Hadoop as if it were SAP technology
HANA Hadoop
What SAP does best: business process (live!)
Vora
“infrastructure”
Organizing For Data
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 63Internal
“When Gartner started to cover BICC as a trend over 10 years ago, it turned out to be one of the biggest success factors for BI programs …
But: “All good things must come to an end.”
The BICC is Also Dead
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 64Internal
So What Replaces BICCs? (According to Gartner)
Long live the ACE:“Analytic Community
of Excellence”!
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 65InternalWho Drives Business Intelligence?
Executives Finance
Operations ITSales
Strategic Planning
Mktg
BICC
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 66Internal
Embrace Shadow IT
Don’t fight back — be a co-conspirator …
40% of users are using an equal amount or more of homegrown applications
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 67Internal
Updating the Traditional BICC to Include Community
A Business Intelligence Competency Center (BICC) is a cross-functional organizational team that has defined tasks, responsibilities, roles, and skills for supporting and promoting the effective use of Business Intelligence* across an organization
* I.e., Analytics, Big Data, Data Science, etc.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 68Internal
It’s About Culture Change First and Foremost
From Power to Empower
From Collection to Connection
From Control to Trust
New BICCs are about providing good governance and encouraging best practice rather than providing reports and analytics
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 69Internal
It’s All About the Relationship!
Conclusion
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Suite
Applications
S/4HANA
DigitalBoardroomIcon
Analytics
C4A
BOBJ
ExtensionsApplicationsIoT
HANA Cloud Platform
(Micro-) Services
IoTPlatform
Identity Management
Business Network
CEC
Platform
HANAEnterprise
Computing Platform
any DB Hadoop
VoraDistributed Computing
Platform
SAP Platform for Digital Transformation
Presentation slides for all ASUG BI + Analytics Conference sessions can be found at:
http://bit.ly/bia16slides
-or- Receive a flash drive with all slide decks if you complete 8 or
more session evaluations in the mobile app.
PRESENTATION MATERIALS
TELL US WHAT YOU THINK
TAKE THE SESSION SURVEY:
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Download the app from iPhone App Store or Google Play.
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Thank You!Timo ElliottVP, Global innovation Evangelist
Timo.Elliott@sap.com @timoelliott
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