Tag Archives: subsetting

Top 5 Benefits For Making Big Data Small

Lean Data Management is a new approach to managing your data growth. It uses the “Lean” concept that originated with Toyota car manufacturing in the 1990’s. The “Lean” concept is based on maximizing efficiency, eliminating waste and providing more value to the customer. (See Informatica’s lean integration solutions as well as John Schmidt’s 10Weeks to Lean Integration blog series.)

As technology has evolved, industries consolidated, and corporations have grown, these organizations are faced with explosive data volumes called “Big Data”. Big Data is all the different types of data that are supported by IT organizations. Applying the “Lean” concept to managing application data will help you reduce the size of your Big Data by archiving live production databases, subsetting non-production databases and archiving/retiring legacy and redundant applications. Informatica’s Lean Data Management approach to reducing Big Data is an effective, comprehensive approach to addressing the challenges created by Big Data. It’s time to Make Big Data Small with Lean Data Management.

Here are the top 5 benefits for Making Big Data Small: (more…)

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Posted in Big Data, Database Archiving, Ultra Messaging | Tagged , , , , , , , , , | Leave a comment

Subsetting Oracle And SAP Applications

In my previous blog, we talked about the benefit of making subsets of test data from live production applications and masking them to address cost and security issues.  When the applications have simple data models where subsets can be made using a simple query on a few tables, the need to implement or purchase a solution may not be warranted.  When dealing with complex custom or packaged applications such as Oracle E-Business Suite or SAP, functional test cases are typically organized by business processes, organization, time, or a combination of each.

Complex custom applications or packaged applications contain data for multiple business processes, such as Accounts Payables or Receivables, Sales & Distribution, or Payroll.  Developing a SQL query that selects a complete subset for each of these processes for a particular business unit or geography and then masks the data while insuring the test application will continue to function is NOT a trivial task.  It requires a detailed knowledge of the data model – including all database constraints, primary and foreign key relationships, data dependencies on programs running in the application tier and any inter-application dependencies via database links or other interfaces.  It is possible to develop internally, but the time and effort required to develop and test makes the cost benefit of subsetting moot. (more…)

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Posted in Application ILM, Data masking, Data Privacy | Tagged , , , , , , , , , | 1 Comment