Data Governance


Data Governance is about defining and continuously improving the lifecycle policies, processes, rules, and roles by which data is managed and consumed across the organisation. Data has become a critically important asset for organisations to leverage, to innovate and increase productivity. Data Governance is required to establish an understanding, manage access, change, and maintain the trust that establishes and sustains value Human and system-generated data enters the business as raw material and through governance becomes valued, trusted. Data Governance helps ensure that the best data is fit for purpose, by the right people, enabling the business to harvest its value to drive growth. Data Governance reduces the risks that arise from improper use of data, breaches of privacy regulations, or the inability to attest to data accuracy as required by regulations or industry standards. BENEFITS • Speeds time to trusted data value • Increases business agility • Reduces risk of noncompliance • Decreases cost of data storage, processing, and management • Allows Business to manage the growing amount of data

“You can’t do analytics on data that you can’t find, and you can’t govern what you don’t know.”

Catapult BI understand data governance spans both IT and Business, each often having different priorities and desired outcomes. A mechanism such as an Enterprise Data Catalogue provides a starting point for this collaboration. 

Catapult BI’s data governance framework includes the development or enhancement of a data catalogue as the source of truth to understand the enterprise information landscape. The catalogue, that will ultimately be matured into the core metadata capability, is the platform to base future data governance decisions such as data maturity assessments, data quality improvements and reference and master data activities. After establishing the metadata capability, the data governance framework overlays the entire data landscape, not just parts of it. 

With these core capabilities established further programs of data improvement can then be undertaken with increased confidence and increased likelihood of success.