Last time we defined current data architects’ tasks: metric clarity ensuring, information sources identifying and managing, consistency ensuring, maintaining relationship among terms,

How to solve them?

The main tool for these tasks solving is knowledge about corporate data landscape, information consuming and accessing processes, «data mechanics» that can be used to develop the convenient report and analytic environment.

There are 3 elements of corporate information knowledge governance:

1. intelligent data collecting;
2. data organization and enhancement;
3. high usability.

All these 3 elements can be possible with data governance technologies and methods as:

• Data storage environment research across the enterprise to identify and inventory data assets;
• Identified data assets profiling to collect structured metadata, data quality estimation, semantic tags identification, potential problems definition;
• Documenting object metadata including data owner information and aspects its origin;
• Data elements classification by every structured element of data asset estimation and attaching to the appropriate business term;
• Indexing and providing of the searchable semantic registry of business glossary terms and elements;
• Quality and usability audit of every data asset element. It provides a possibility to rapidly create reports of the actual performance measures for data quality compliance.

Such methods usage allows to create a corporate data catalog that provides different benefits with data consumers. This catalog is a repository for data assets inventory. It also serves as an enterprise resource and with its help data architects and consumers can share knowledge. It documents the high-level object metadata, identifies data elements and maps them to the semantic business glossary. This information can be used into an intelligent search that allows consumers to browse data assets, define more suitable data sets for reporting and analytics for every business scenario.

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