What is Data governance?
Data Governance, is the act of actively managing and monitoring the data that exists within an organisation with the goal of ensuring Trusted Data, that is understood, accessible, transparent, compliant and protected. Achieved through the definition and application of rules, policies and procedures that when combined with people and processes are collectively known as Data Governance.
Trusted data needs to be compliant, complete, accurate, transparent and appropriate. To achieve this needs to be actively monitored and managed. To monitor you need to discover, understand and catalog with definitions, rules policies and responsibilities. To manage and protect you need to have roles, responsibilities, ownership and processes to ensure that rules, policies and definitions are applied and remediation applied when not compliant.
It would be a mistake to assume that Data Governance technology alone is the solution when in fact it’s simply an enabler. The solution is a combination of people, processes and technology built on analysis, design and modelling.
Our journey with Data Governance started 20 years when building Data Warehouses was in its infancy. We learnt quickly that building data warehouses with trusted information that users would be prepared to adopt required more than load scripts and agile data modelling. It also needed data quality, data transparency, a common understanding of business language, and sophisticated access models. These requirements have only recently been termed ‘Data Governance’, but as a business, we have always been being applying these disciplines to our customers’ assets and solutions. Before the advent of the tools we delivered Governance in documents, spreadsheets and our database models.
Data Governance Activities
- Redacting / obscuring
We are very flexible in our engagement approach from short term tactical help to help issues or get you started to a more involved end to end pilots that help you learn while delivering something that is meaningful and useful.
However, whatever you want to do, we believe in not trying to do too much at time, so we recommend breaking down your projects into smaller chunks of easily defined and scoped deliverables. This enables you to focus on the detail, have early delivery of results and capability and manage better manage time and cost. As you do this your understanding of how and what you want to do will grow and your thoughts and approach may change, the approach enables you to adapt without major rework.
Examples of SmallNet Data Governance Engagements:
- Data Lineage for financial services and Banking organisations to support regulatory compliance
- Business Glossary of terms and Policies, setup and population
- Catalog design and population and initial load from existing sources such other catalog tools, spreadsheets and word documents etc
- Process and workflow implementation
- Data Quality Platform to support the active monitoring and remediation of Data Quality failures
- Technical Architecture and solution design
- Strategy and Implementation road map, helping to build a Data
- Governance Health Checks and Readiness Assessments