[Data Rationalization]

Data Rationalization allows organizations to reduce cost by simplifying their data ecosystems.

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The Problem

Large organizations often possess thousands of databases, acquired through decades of organic growth or M&A activity. In addition, many of these databases contain redundant data.

The Remedy

Data Rationalization allows organizations to simplify their data landscape, systematically eliminating redundant databases and significantly reducing data management costs. It creates a path toward greater efficiencies and lower costs through:

  • Decommissioning databases with obsolete, duplicate, non-critical or otherwise unused information
  • Rationalizing databases that have similar information but are critical to the business
  • Protecting and monitoring critical databases that contain core business information

redundant database information

data rationalization solution suite

Our Solution

The Data Rationalization Solution Suite (DRSS) is a comprehensive suite of applications that allows organizations to rationalize their core databases in a systematic way.

In order to create a foundation for rationalization, DRSS performs four core activities

  • Data Discovery
  • Data Profiling
  • Data Quality
  • Master Data Integration

Once these activities are complete, candidates for decommissioning and rationalization are identified. A program is initiated to systematically reduce cost by reducing the number of databases that need to be maintained.


In contrast to traditional manual approaches that focus on reducing costs in silos, Global IDs software reverse-engineers the data ecosystem to identify candidates for database rationalization. Since data ecosystems are large and complex, reducing costs from these environments has a significant ROI.

This perspective allows organizations to see their enterprise data in a holistic manner, allowing visibility into the way in which business is conducted across the enterprise.

Our machine-centric approach to data governance is much more cost-effective than traditional approaches. It is:

  1. Automated (greater than 90%)
  2. High speed
  3. Continuously evolving (through increased awareness of the data landscape)

Some of the world's largest organizations have used this approach to bring transparency and visibility into complex data landscapes.

Improving ROI through Data Rationalization
Global IDs data rationalization is like pulling back the curtains and getting the giant panoramic view of a vista you’d only seen before in pieces. Only when you can see and appreciate the data landscape in its entirety can you begin to make thoughtful and intelligent decisions based on what the data can do for your business. - Arka Mukherjee, Founder and CEO

Next Steps

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