Passionately curious about Data, Databases and Systems Complexity. Data is ubiquitous, the database universe is dichotomous (structured and unstructured), expanding and complex. Find my Database Research at SQLToolkit.co.uk . Microsoft Data Platform MVP

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Wednesday 9 February 2022

Data Governance By Stealth

Listened to an interesting discussion on data governance in the Data Governance By Stealth – Aligning the Data Governance and Data Strategy Roadmap webinar with 

  • Andrew Crossley
  • Alex Kontofrios, Head of Data Governance at Close Brothers
  • Kat Holmes, Former Data Director at ITV and founder at MenopauseX
  • Danny McCarthy, Head of Data Management at ClearBank
  • Stephen Maguire, Data Governance Specialist at the Oakland Group

There were an number of interesting point and discussion on the different ways data governance is addressed within business. Data governance is that word that should not be mentioned. 

A way to start discussion could be through  using the data ethics canvas that the ODI developed. It can be a way to find a lever or hook.

Key points raised to help you get started are 

  • data governance needs to be invisible
  • there is no boiler plate culture for this to work
  • it needs to be explained in layman's terms

Another insight was don't get involved in a data governance project unless it is helpful to the business.

The establishment of committees\boards is not required to start. These will come but initially it needs to be an agenda item on a meeting or project.

Don't talk about data governance, but business value for great data.

Data governance needs to be simple messaging.

It is key that everyone understands that data governance underpins all data tasks.

There was an interesting point that the data dictionary should be a part of the organisational structure.

Data literacy is important to improve business. People need to know how to structure questions.

Don't follow a framework as every business is different.

Follow an agile incremental delivery.

Start with a data readiness assessment with four areas:

  • usage
  • data quality
  • controls - non functional requirements
  • business readiness

two core questions that are trying to be solved are 

  1. what business problem are you trying to solve
  2. secondly, identify problems that using tooling would help solve

There was a difference in opinion on whether deploying a technical tool was first or second thing to look at. Although this helps with things it brings about the need for a technical team to support it and skilling issues that need to be addressed.

Data Governance specialist must be technology experts in this new world. The new role closely aligns to the Data Architect role. 

Use a standard ontology to use standard language.

It is important to not start building an in depth data dictionary model. This does not help solve the business requirements or provide value to the business.

Having a standard blueprint is a blocker to success. 

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