ibis 2015 final template

Real-time BO Universe to Cloud Data Sources

Sumit Sarkar (@SAsInSumit)Chief Data Evangelist, DataDirect

Experience with Data Connectivity for BI

Talk to BI communities across Oracle, SAP, IBM, Microstrategy, Tableau, JasperSoft and Qlikview.

Advocate for BI professionals at shows across Dreamforce, Hadoop Strata and MongoDBWorld

Contributor to TDWI, Odata.org, Oracle Data Integration, Salesforce Developers, Progress Data Connections, and Microstrategy

DataDirect ODBC, JDBC, OData for Disruptive Data

Big Data/NoSQL Apache Hadoop Hive

Cloudera Hortonworks MapR EMR

Pivotal HAWQ MongoDB Cassandra SparkSQL Apache Solr*

Data Warehouses Amazon Redshift SAP Sybase IQ Teradata Oracle Exadata Pivotal Greenplum

Relational Oracle DB Microsoft SQL

Server IBM DB2 for I IBM DB2 for z/OS IBM DB2 for LUW MySQL MemSQL PostgreSQL IBM Informix SAP Sybase Pervasive SQL Progress OpenEdge Progress Rollbase Splice Machine* IBM DashDB*

SaaS/Cloud Salesforce.com

Database.com FinancialForce Veeva CRM ServiceMAX

Hubspot Marketo Microsoft Dynamics

CRM Microsoft SQL Azure Oracle Eloqua Oracle Service Cloud Google Analytics Netsuite* SQL over HTTPS

In-Memory MemSQL SAP HANA Oracle TImesTen* VoltDB*

Agenda

1- Introduction to SAP Business Objects Cloud Universes

2- Architecture options for Cloud Universes

3- Best Practices and Lessons Learned

Goals

1- Understanding of a Cloud Universe

2- Be the thought leader on cloud data sources.

1- Introduction to SAP Business Objects Cloud Universes

a. What is a Cloud Universe?

b. Common Cloud Data Sources

c. Common use cases in production

Introduction: What is a cloud Universe?

Introduction: Common cloud data sources for BOBJSaaSSalesforceVeeva CRMNetSuiteServiceNowCloud9WorkDayTavantKinaxis Rapid ResponseCloud DatabasesAmazon RedshiftSQL Server AzureHosted DBs

Introduction: Common Use Cases

•Salesforce reporting (native reporting inadequate)•Migrating/Consolidating BI Platforms to Business Objects•Real-time data blending in MSU to supplement the Data Warehouse with real-time Salesforce data•Real-time Mobile Universe Web Intelligence

2- Architecture options for Cloud Universes

a. Real-time / Direct

b. Data Warehouse

c. Staging Database

d. Hybrid (Real-time and Data Warehouse)

e. Pros/Cons

Architecture: Real-time / Direct

UNIVERSE

Architecture: Staging Databases

UNIVERSE

Architecture: Data Warehouse

UNIVERSE

Architecture: Data Warehouse and real-time

UNIVERSE

Architecture: Pros/Cons

Real-time Direct

Data Warehouse

Staging Database

DW and real-time (MSU)

Self Service Y

Rapid Development

Y

Real-time Y Y

360 view Y Y

Local Connection

Y Y Y

Architecture: SaaS ODBC3 Universe ConnectionIDT/UDT – 32-bitApp Server/BODS – 64-bit

3- Best Practices

a. SaaS data sources are not relational databases or MPP warehouses (non-optimized joins)

b. How to handle authentication

c. Keeping up with the APIs

d. Real-time versus ETL (MSU and SSU)

e. Understand road map for new SaaS applications

Best Practices: SaaS APIs vs databases

• Determine if SaaS source has a query language

• What relationships are exposed between objects

• Capacity planning for larger in-memory operations

LESSONS LEARNEDModeling Universe on top of unrelated objects from any SaaS application with large data volumes will be a challenge – not really different from RDBMS.

Best Practices: Authentication

• Salesforce shops typically setup a common BI user

• Single Sign-On requirements

LESSONS LEARNEDHow to delegate BOBJ SSO to Salesforce SSO?

Best Practices: Keeping up with the APIs

• Find out how often APIs change for your SaaS source

• Schema management for new objects/fields• Refresh schema?

• Understand API call limits for 24 hour period

LESSONS LEARNEDSalesforce API changes quarterly and requires updates to connectors to support latest fields/objects. This is reason native connector with BODS does not work well.

Best Practices: Real-time versus ETL

• Understand the performance of the APIs

• What data volumes are required?

LESSONS LEARNEDPulling very large data volumes in activity and lead records from Eloqua or Marketo for a real-time Universe is not practical.

Best Practices: Know your data road map

• Demonstrate thought leadership by showing what SaaS sources you can support.

• Understand the SaaS BI landscape by department to compare contrast your services.

LESSONS LEARNEDDepartments may not engage BOBJ group and duplicate BI efforts further fragmenting the data intelligence.

Resources

• Blog tutorial to create a Salesforce Universe: https://blogs.datadirect.com/2012/05/sap-business-objects-universe-to-salesforce-crm-database-com-force-com.html

• Blog tutorial to create a Marketing Universe: https://blogs.datadirect.com/2014/01/sap-business-objects-universe-marketing-data-eloqua-marketo.html

• Blog tutorial to integrate BO Data Services with Cloud Sources: https://blogs.datadirect.com/2015/02/sap-bods-linux-salesforce-com-netsuite.html

Love to hear from SAP BO community!

www.linkedin.com/in/meetsumitSumit.sarkar@progress.com

@SAsInSumit919-461-4284