SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
Ibis 2015 final template
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
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
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
Notas del editor
Focus is on open data industry standards
Synopsis
The explosion of Cloud Data Sources such as Salesforce.com, Google Analytics, Marketo, Eloqua, etc are disrupting BI infrastructure; and business sponsors are turning to one-off BI solutions further fragmenting reporting capabilities. Learn best practices and common gotchas for SAP Business Objects shops looking to establish robust connectivity from Single or Multi Source Universes to cloud data; and take back control of future BI projects. With the Universe, learn how to create a direct and real-time connection to all business systems across the enterprise and in the cloud. Leverage existing skills and infrastructure to consume cloud data; and establish your group as the thought leader on cloud data sources. Discussion is focused on cloud connectivity achieved with ODBC3 relational sources with third party ODBC drivers from leading vendors in the space.
BOBJ and Crystal projects with NoSQL sources such as MongoDB
No Marketing?? (Google Analytics, Eloqua, Marketo, Pardot)
One version of the truth and “self service”.
Stanford TDWI story
Mobile Webi reports delivered to 600 ipads
Helps supplement poor SaaS APIs not suitable for heavy duty workloads
Easyl and Eloqua?
BODS to Salesforce/NetSuite are common projects
ETL platform
Moving data into EDW or SAP HANA
Starting to see Hadoop as well
Progress Software does this:
Sales Management Dashboards are pulled in real-time
Business Review data is pulled from archives
Create Project
Create New Database Connection
Create Data Foundation Layer
Insert Tables and Joins into DFX layer
Create Business Layer
Create Folders, Classes and Objects (Dimension, Detail, Measure) in BLX layer
Creating queries to test
Publish to Repository
Worked with 30+ SAP shops integrating cloud data sources over last 3 years.