How do you implement a successful data governance programme?
1. AnalyseData profiling: This process of gathering and examining information about existing data is often viewed as a pure data quality activity. But when shared with those responsible for the data this can give advanced business expertise and insight to the results – bringing wider benefits to the organisation as a whole. Reviewing and approving data definitions: To understand and manage your data it must be defined (for example, in a data dictionary or glossary), and then held where it is readily accessible by the users.
2. ImproveReviewing and approving business rules for data cleansing: After undertaking your analysis you will need to garner input from your stakeholders to agree the rules by which the data will be cleansed. It’s also useful to include these data cleansing rules in your data glossary for ease of future reference. Master data management: Make sure the processes, governance, policies, and standards used are well defined and communicated.
3. Take controlDefining data quality rules: This pro-active process will enable you to report on the status of your data quality at any point in time – not only serving as a monitoring system, but also providing an early warning of any potential issues (before they get too big – and expensive!) Data quality reporting: Only after data quality rules are defined will you be able to instigate a process for reporting on how the data measures up against those rules. Monitoring and acting on data quality reports: Here is where the chain comes back full circle to the initial establishment of a policy on data governance. With this, and the associated processes, in place you can take steps to ensure that those that need to take the necessary action, do so. Taking these steps, and embedding them within your organisation will help to ensure that data quality and governance become entwined in a symbiotic relationship. This will help to deliver long-term benefits for the organisation as a whole, and help you to capitalise on the benefits that data quality can bring in a sustainable manner. Janani Dumbleton is principal consultant of data quality propositions at Experian UK.
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