The Intelligent Business Blog

In many multi-part series, I will lay out the design for the Enterprise Data Warehouse from an Oracle eBusiness Suite. Obviously, these will be by business areas. I will start with the core financial module – the General Ledger. Let’s try to put a structure to each of these series:

Part 1 – Functional Overview
Part 2 - Key Reporting / Analyses
Part 3 - Target design and considerations
Part 4 – Source Schema, Key queries, ETL maps, business rules
And more as needed for the topic under discussion.

Part 1: A short Overview of Oracle General Ledger:

The General Ledger (GL) is at the heart of the Accounting system of Oracle eBS. The main purpose of GL is to record financial activity of the company and to produce financial and management reports. The GL consolidates financial information from all other transactional modules or subledgers and maintains summary level information. For example, it stores the accounting information for a Receivables invoice or an invoice payable to a vendor. It stores accounting entries for expense for depreciation of an asset or an inventory transfer. It also has accounting entries made within itself using journal entries.

If you want to know more on Oracle General Ledger, or any other Financial module, refer to the latest User Guide (pdf file) or the Oracle E-Business Suite Financials Handbook, a handy reference that I highly recommend to anyone who wants a thorough understanding of the functional concepts of the financial modules within Oracle eBusiness Suite.

The following diagram is a high level overview of how some of the core modules interact with each other within Oracle Financials:
http://intelligentbusiness.files.wordpress.com/2008/06/gl_int1.gif

Source: 11i Financial Functional Foundation

Let us dig a little deeper (more…)

Yes, it is time for me to stick my foot in the Kimball vs. Inmon debate. Many people have debated these two methods of building a data warehouse, including Kimball himself in this article in the Intelligent Enterprise magazine.

I am not indoctrinated to either approach. The Inmon approach works very well if you have to extract data from many different source systems, and you need an integrated business model to control the common business definitions better. In such cases, it might be very helpful to model the transactions in a third-normal form (3NF) data warehouse (or Corporate Information Factory) to reflect the whole business. In my opinion, Kimball’s overlay on Inmon (build the atomic level dimensional data warehouse with conformed dimensions from this 3NF data warehouse) is a redundant and in most cases, a wasted effort. To succeed with BI from this 3NF data warehouse (or the CIF), you need to build cubes or aggregate-level dimensional data marts. For detail-level atomic data, it is not too difficult to write a report from the CIF.  There are many examples of this, like the pre-built data warehouse solutions for industries like retail or telecom from Oracle.

For data warehouses or marts that are focused on one enterprise or department, and those that are built from ERP systems like Oracle eBusiness Suite, the Kimball approach of building a data warehouse as a collection of data marts linked together with conformed dimensions is more suitable and, is easier and cheaper to build. (more…)

I came across this interview of Bill Hostmann, research vice president and conference chair of the Gartner Business Intelligence Summit, held this week in Chicago. This set me thinking today over lunch. Here’s what he says:

“The big message is going to be around tying together information, decision making and performance management. How do we get at the right information to make the right decisions that will drive the performance that the business demands? That’s a shift from the traditional business intelligence focus, which was about query tools, reporting tools, OLAP and data-mining functionality sitting on top of a data warehouse or data mart used by analysts”.

How many of us, who are engaged in this field, think that traditional business intelligence is all about query tools, reporting tools, OLAP and data-mining? Business intelligence has always been about tying information together, eliminating data silos, and enabling the organization make better decisions. Whether they are tools like Oracle BI, or Cognos, or Business Objects or applications like Sales Analyzers, Performance Applications, Budgeting and Forecasting, they have all been about providing the right information and analyses to the right people at the right time. The core purpose of Data Warehousing, Business Intelligence and Data Mining   has always been to help companies make intelligent, informed and insightful decisions. It was never about the tools.

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This is my first post here on this blog. Over the next few weeks, I will focus on how to build an integrated business intelligence platform for Oracle eBusiness Suite - I will initially focus on the Sales and Finance subject areas, as these are the most commonly built data marts in an Oracle Apps environment.

Before I get into any designs, let me spend some time discussing why any company that has Oracle Applications would want to build an Enterprise Data Warehouse. Doesn’t Oracle have it already? The short answer to that is – Yes. The long answer to that would be – Not really.

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