With an increase in the adoption of cloud applications by
large corporations, most organizations today are in some form of hybrid state
i.e. they are using a combination of both on-premise as well as cloud
applications to run their business.
Regardless of where the applications maintain their data,
organizations need the ability to see a complete view of the company spanning
across different parts of the business, which in this case would be combining
insightful data across on-premise as well as public cloud instances.
To take some examples:
1. Combining HR and Financials data to analyze Revenue per employee
2. Combining Sales and Financials data to create customer Scorecards
3. Combining Sales and Order Management data to improve your demand planning system
4. Combining your Sales and Financials Data for Forecasting
1. Combining HR and Financials data to analyze Revenue per employee
2. Combining Sales and Financials data to create customer Scorecards
3. Combining Sales and Order Management data to improve your demand planning system
4. Combining your Sales and Financials Data for Forecasting
In
this article, I would like to present multiple design approaches that other
organizations have successfully used to consolidate data from multiple cloud
and on-premise applications and to perform seamless analytics across these
varied data sources.
If you are attending Collaborate15 (#C15LV),
please join me to discuss this topic and case studies of what
other organizations are doing to address this challenge.
What is Cross Functional analysis?
Cross functional analysis is the ability to gather
valuable business insights by efficiently joining both CRM and ERP data that
are used to run front-office and back-office applications for an organization.
Shown
in Figure 1 below is an example of cross
functional analysis used to build a “Quarterly
Revenue Forecast Report” for a Services Company that has three Business
Units and Runs Oracle Cloud to manage its CRM and Oracle EBS to manage its
Financial Processes.
Figure 1
Data Consolidation Options
There
are multiple options you could consider to fulfill cross functional analysis
by pulling information
from a variety of source systems. Here, I would like to discuss the following
two options:
1.
Consolidating
all your insightful data on Oracle Business Analytics warehouse and using
on-premise OBIEE to perform analysis
2.
Consolidating
your data on Oracle Cloud Database schema and using Oracle BI Cloud Service
(BICS) to perform analysis
The
top half of Figure 2 below shows
multiple cloud applications. The top lefts shows various cloud applications where
data is generated and hosted. The top right shows the current Oracle cloud
analytics platform that can be used to perform reporting.
Likewise,
the bottom left shows multiple on-premise applications that create data on an
on-premise instance. The bottom right shows OBI Application being used to
perform reporting.
Figure 2
Option 1 - Consolidating all your insightful data on Oracle Business Analytics warehouse and using on-premise OBIEE to perform analysis
If
you’re using all on-premise applications to run your business, you can use your
existing Oracle BI Applications ETL process to extend into non-oracle data
sources.
If
you’re in a Hybrid state using some cloud applications to run certain parts of
your business, you can use cloud ETL (Extract, Transform and Load) tools to
move your data onto on-premise staging tables, followed by Oracle’s prebuilt
adaptor to push the data onto corresponding Star Schemas.
You
might want to choose option 1 to move your public cloud data (Salesforce,
NetSuite, Oracle Applications cloud) on to Oracle Business Analytics warehouse
(OBAW) if you have already deployed Oracle BI Application and are using its
Data Model to consolidate to non-Oracle data sources.
Data Movement
Technology
There
are number of technologies you can use to move your public cloud data to an on-premise
Data Warehouse staging table. Oracle has recently released a number of technologies
and approaches that can be used for this purpose. The technology to move data
between Cloud and On-prem instances is constantly evolving.
As
shown in Figure 3 below, in order to
consolidate the data into an on-premise Oracle Business Analytics Warehouse, we would continue to use Oracle’s pre built
adaptor to go on to oracle ERP sources, and use one of the newly released Data
Movement technologies to move data from cloud to a common staging table.
Figure 3
Design Considerations
1.
Use
Staging tables to consolidate data from multiple applications(on-premise /public
cloud)
2.
Leverage
BI Apps Data Model
3.
Leverage
Common dimensions for analysis across applications
4.
Assign
Unique Data Source Number for each distinct applications
Option
2 - Consolidating
your data on Oracle Cloud Database schema and using Oracle BI Cloud Service
(BICS) to perform analysis
If
you are considering cloud to build your enterprise analytics platform, there
are number of Data Movement technologies that can be used to consolidate your
data on Oracle’s cloud based database schema service.
The
approach here would be similar to the one discussed in Option 1, the difference
being, we will consolidate the data on Oracle Cloud based Data Base schema
Service.
Figure 4
Cloud
technology is the next critical evolutionary step in software. It’s a trend
that has momentum to become the dominant platform of the future. If you are
interested in learning more about why you should consider cloud to build your
enterprise analytics platform, you can view my earlier post here on modernizing your analytics platform on
Oracle BI Cloud Service.
