Data Governance

Data Governance

Data Governance

The data analysis is based on data, but what would happen if the data was not verified “form trusted source”? certainly, the results won’t be accurate or not right at all and the business intelligence won’t be of value, that’s why we offer our clients data governance solutions which are related to managing three factors which are data availability, the ease of using and safety these data, and at the end ensuring the access to trusted and accurate data that help in making accurate decisions, for instance: the name of a client could be mentioned in different ways within the company’s systems such as Mr. Ahmad Mohammed or Ahmad Mohammed and both of them are for the same person but the only difference is the title which could lead to a problem in the data integration and therefore not trusted or accurate data and such problems could paralyze the business intelligence system and here where the role of data governance comes to solve these kinds of problems.

If anyone of the following item has an impact on your business, then your organization needs DATA GOVERNANCE

- Business transformation (needed to survive in today's digital world)
- Constantly changing Governance regulations
- Data related Risk management and compliance
- Industry consolidation (Mergers and Acquisitions)
- Margin pressure (Particularly in Telecom Business)
- Agile data-driven competitors picking off high-margin markets.
Also in order to be a cost-effective, measurable, transparent and sustainable organization

Change is the only constant especially in today’s digital world.

Where can Data Governance lead to?


Data Ownership and responsibility clearly defined


Restricted data is accessed by authorized and authenticated and relevant department users


Improved data accessibility and responsiveness


Data is correct


Data is consistent


Data is integrated


Data values comply with the business rules


Data is well defined and understood


Planned data redundancy


Improved data consistency


Increased data sharing


Increased application and development productivity


Enforcement of standards


Improved data quality


Reduce redundant efforts


Improved decision support