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What Data Governance roles do you need to make your Data Quality initiative a success?

NICOLA ASKHAM EXPLAINS THE ROLES WITHIN DATA GOVERNANCE

In my last blog I shared a couple of questions I frequently get asked about data governance around whether data governance is the same as data quality and if you need both. When I have convinced the organisations that I am working with that they do indeed need both, one of the most common questions I am asked is:

What data governance roles do we need to make our data quality initiative a success?

My initial response may seem pernickety, but I do think it is important to focus more on the data governance responsibilities than role names. But I do agree that having role titles can significantly facilitate this. If you read my blogs or have attended one of my training sessions you will be aware that I am not precious about the names given to data governance roles (it is much more important to focus on what they are doing, rather than argue over what they are called!) However, using some best practice role names is always a good place to start and gives convenient labels to make it easier when discussing this topic.

So whilst the role titles may differ and it may suit some organisations to combine or split these roles, the following are a good set of best practice data governance roles:

owner
Data Owner(s)

These will be senior people within your organisation who have signed up to be accountable for the quality of a defined dataset. For example, you may have your Finance Director as the Data Owner for finance data in your organisation. In order for this role to have the authority it needs, it should be undertaken by senior individuals. However, this level of seniority means that they are unlikely to have the time to be involved in data quality activities on a day-to-day basis. For this reason they are likely to be supported by one or more Data Stewards.

steward
Data Steward(s)

The main difference between a Data Owner and a Data Steward is that the latter is responsible for the quality of a defined dataset on day-to-day basis. For example, it is likely that they will draft the data quality rules by which their data is measured and the Data Owner will approve those rules.

producer
Data Producer(s)

Most people in an organisation are responsible for creating or capturing data and it is important that they understand that they must do so in accordance with the Data Consumers’ requirements.

consumer
Data Consumer(s)

These are the people who are using the data. It is important that the data is good enough for them to do their job, but they have to be responsible for defining what makes the data good enough to use.

 

Here I offer more in depth advice on how to identify the correct data owners for your data governance programme.

Also if you want to get ahead in the data governance game, try the Experian Pandora Free Data Profiler, which was voted the most powerful data profiling insight tool on the market by Bloor.