Data Management

Data Management can mean different things to different people: at times it is synonym for data governance; in other cases it is equivalent to master data management.

For us, Data Management is an approach that implements an analytic framework that delivers quicker access to results and deeper insight, built on the following three pillars:


Any data initiative begins with identifying clear objectives and the strategy to pursue such objectives. Questions such as should we implement master data management or should we use an agile approach are answered.
The current state is reviewed, an ideal state is envisioned, and a high level roadmap to reach that ideal state is crafted.


Governing data entities requires identifying subject matter experts, data owners, data stewards, users types, access permissions, and tools as well as determining the rules for creating and manipulating data assets.


The way the data is modeled affects its management and usability and we adhere to the principles first proposed by the Kimball Group and related to dimensional modelling. Supported by strong governance, this approach eliminates duplicate work, creates a single version of results, and allows for the sharing of business entities (through conformed dimensions) that can be used to implement a straightforward master data management policy