In Part 1, we saw an overview of Data Governance and the initiatives firms need to take to incorporate governance. Let’s now look a bit more in detail about Data Quality Management as this is a key step in Data Governance towards ensuring data quality.
Why is Data Quality Management necessary?
Data Quality Management is the process of establishing roles & responsibilities and the business rules that govern data by bringing the Business and IT to work together. Their task is two-fold:- to address the problems that already exist and to prevent the potential ones from occurring. Let’s focus on the roles & responsibilities as this forms the core of a Data Quality Management program.
Roles & Responsibilities
There are various roles involved in this process and all of them have to be accountable to ensure data quality. Its vital that the roles are clearly defined upfront. The following are some of the commonly recognized roles:-
- Data Governance Council – comprises of an Information Management Head and Data Stewards from various units.
- Information Management Head – is the one who is accountable to the Governance Council on all aspects of data quality. This role would typically be fulfilled by the CIO.
- Data Stewards – are the unit heads who lay down the rules & policies to be adhered to by rest of the team. This role would usually be fulfilled by a Program Manager.
- Data Custodians – are responsible for the safe storage & maintenance of data within the technical environment. DBA’s would normally be the data custodians in a firm.
- Business Analysts – are the ones who convey the data quality requirements to the data analysts.
- Data Analysts – are those who would reflect the requirements into the model before handing it over to the development team.
Some best practices to successful data governance
This article on CIO.com talks about some of the best practices around successful data governance. They key steps include:-
- Get a governor and the right people in place to govern
- Survey your situation
- Develop a data-governance strategy
- Calculate the value of your data
- Calculate the probability of risk
- Monitor the efficacy of your controls