“Those that establish a formal Data Governance program, exercise authority and control with great intentionality, are better able to increase the value they get from their data assets.”- DAMA DMBOK-2. Data governance strategy is a practice of exercising authority, control and shared decision making, including planning, monitoring and enforcement, over the management of data assets.
At Catapult BI, we offer tailored Data Governance and Data Management services to our clients, guided by the DAMA International – Data Management Body of Knowledge (DAMA – DMBOK).
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It is important to frame a strategy in accordance to Data Governance
framework, to enable the entire enterprise function as one single unit, for
more cohesive and optimum benefit. Catapult BI’s core practises to implement this system are:
The process of managing shared data to meet organisational goals, reduce risks associated with data redundancy, ensure higher quality and reduce the costs of data integration, is referred to as MDM. Catapult BI’s vision to achieve the outcomes is to:
All a part of Information Lifecycle Management, it is essential to follow these 3 steps to ensure that right data is put to right use in the right form. At Catapult BI, our experts define each of the terms as:
The planning, implementation and control of activities that apply quality management techniques to data in order to assure it is fit for consumption and meets the needs of data consumers is referred to as Data Quality analysis. As important as it sounds, Catapult BI believes that monitoring this changing quality of data is equally beneficial to improve the business systems. Our experts analyse DQ on the basis of:
Data stewardship involves the exercise of authority, control and shared decision making over the management of data assets. Catapult BI’s Data Stewardship practises include:
It involves planning, implementation and control activities to enable access to high quality, integrated metadata. Catapult BI believes that it is important to-
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