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?

1

Data Ownership and responsibility clearly defined

2

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

3

Improved data accessibility and responsiveness

4

Data is correct

5

Data is consistent

6

Data is integrated

7

Data values comply with the business rules

8

Data is well defined and understood

9

Planned data redundancy

10

Improved data consistency

11

Increased data sharing

12

Increased application and development productivity

13

Enforcement of standards

14

Improved data quality

15

Reduce redundant efforts

16

Improved decision support