The document discusses the integration of cloud data sources with SAP BusinessObjects, outlining architecture options and best practices for managing cloud universes. It emphasizes understanding cloud universes, real-time data blending, and handling authentication, along with lessons learned from using various SaaS databases. Various resources and examples are provided to assist professionals in the BI community with implementing these integrations.

1. Real-time BO Universe to
Cloud Data Sources
Sumit Sarkar (@SAsInSumit)
Chief Data Evangelist, DataDirect

2. 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

3. 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*

4. Agenda
1- Introduction to SAP Business Objects Cloud
Universes
2- Architecture options for Cloud Universes
3- Best Practices and Lessons Learned

5. Goals
1- Understanding of a Cloud Universe
2- Be the thought leader on cloud data sources.

6. 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

7. Introduction: What is a cloud Universe?

8. Introduction: Common cloud data sources for BOBJ
SaaS
Salesforce
Veeva CRM
NetSuite
ServiceNow
Cloud9
WorkDay
Tavant
Kinaxis Rapid Response
Cloud Databases
Amazon Redshift
SQL Server Azure
Hosted DBs

9. 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

10. 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

11. Architecture: Real-time / Direct
UNIVERSE

12. Architecture: Staging Databases
UNIVERSE

13. Architecture: Data Warehouse
UNIVERSE

14. Architecture: Data Warehouse and real-time
UNIVERSE

15. 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

16. Architecture: SaaS ODBC3 Universe Connection
IDT/UDT – 32-bit
App Server/BODS – 64-bit

21. 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

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

23. Best Practices: Authentication
• Salesforce shops typically setup a common BI user
• Single Sign-On requirements
LESSONS LEARNED
How to delegate BOBJ SSO to Salesforce SSO?

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

25. Best Practices: Real-time versus ETL
• Understand the performance of the APIs
• What data volumes are required?
LESSONS LEARNED
Pulling very large data volumes in activity and lead
records from Eloqua or Marketo for a real-time
Universe is not practical.

26. 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 LEARNED
Departments may not engage BOBJ group and
duplicate BI efforts further fragmenting the data
intelligence.

27. 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

28. Love to hear from SAP BO
community!
www.linkedin.com/in/meetsumit
Sumit.sarkar@progress.com
@SAsInSumit
919-461-4284