Big Data & Analytics

Author

Carlos Barge

The management processes and policies necessary to ensure that data captured or generated within a company is of an appropriate standard to use, represents actual business facts and has its integrity preserved when transferred to repositories (e.g. Data Lakes and / or Data Warehouses, General Ledgers etc.), especially when this transfer involves aggregation or merging of different data sets.

The activities that Data Governance has oversight of include the operation of and changes to Systems of Record and the activities of Data Management and Analytics departments (which may be merged into one unit, or discrete but with close collaboration).

Data Governance has a strategic role, often involving senior management. Day-to-day tasks supporting Data Governance are often carried out by a Data Management team. Data Governance is a framework that comprises of five pillars:

1) Availability
2) Usability
3) Integrity
4) Security
5) Implementation

These processes involve efficient coordination of people and technology in a manner that results in realizing the value of data for an enterprise. It bridges the gap between technology and business — advancing accurate, honest, and secure decision-making.

Although technology is core to data governance, it is only a facilitator, and not crucial for data governance. It has to be applied as a regulated workflow within the firm through people and processes. Without that regulation, data would never be considered a valuable asset.

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