QA success story


Data Aggregation and Preparation Platform

More

accurate payment data due to better rates of data matching via automatch

Cut

operational costs via configurable thresholds for specific tasks

On

time payment of royalties due to faster data preparation

Business Case Summary

A solution had to be created to enable flexible, automated cleansing and matching of usage data against the clients knowledge base in order to facilitate timely/efficient calculation and payment of royalties on multiple rights types in multiple territories.

Solution Summary

We deliverеd an enterprise solution that enables the client to receive, cleanse, store, manipulate and prepare usage (royalty source) and non-usage data received from multiple external sources.

Business Case Story

The client wanted to provide better experience to business users and enhance their ability to access and manipulate data from multiple sources. Their main objective was to replace an existing legacy system with a convenient user interface that provides advanced capabilities for data cleansing, enrichment and matching.

There was a need for a new system with better processing times, higher accuracy and configuration capabilities in order to facilitate ongoing, continuous data flow from various sources to operational systems in other to have shorter distribution cycles to shareholders.

Solution Story

An initial data migration solution was created in parallel with the main application in order to move data from the legacy system and ensure seamless transition. The data aggregation and preparation platform was set up via Ataccama software and includes data quality and data mastering layers, services integrating it with other existing client systems, and two separate user interfaces.

The solution was delivered in 3 releases organized by functionality. Adastra provided design, development as well as quality assurance for each of its components and continues to provide ongoing support in all those areas. From quality assurance perspective there were a few main challenges we had to overcome:

  • Make sure the initial data migration was fully and properly transformed to fit the new system, without having access to the legacy one due to data security sensitivity.
  • Тest a multitude of source file types and incoming streams of data each with their own set of cleansing and validation rules.
  • Create a user defined function library in order to facilitate testing extremely complex data mastering rules.

Benefits Story

After the solution implementation, it is much more convenient for business users to access and manipulate data as well as readily “follow the money” e.g. follow through the distribution chain and trace member royalties back to the source of the associated licensing fees as applicable. There is improvement observable in the following areas as well:

  • Faster incoming data processing time
  • Higher ongoing data match percentages
  • Ability to further configure the data preparation process as needed

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