Ibis 2015 final template
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Transcript of 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