The Definitive Guide To Implementing Data Governance

Recently, I realised, this would be my third iteration of helping organisations implement Data Governance into their company. Surely, there are lessons to be shared here. What are the common steps to be taken? Here’s how I’ve helped companies do it.

What is Data Management

Data Management is an entire methodology on how to handle your data, of which Data Governance is the central component holding everything together.
DAMA – Data Management, the industry body, has a book called DMBOK – the Data Management Book Of Knowledge. In here, the DAMA Dictionary of Data Management defines Data Governance as

‘The exercise of authority, control and shared decision making (planning, monitoring and enforcement) over the management of data assets.’  DAMA has identified 10 major functions of Data Management in the DAMA-DMBOK (Data Management Body of Knowledge). Data Governance is identified as the core component of Data Management, tying together the other 10 disciplines, such as
Data Architecture,
Data Modelling and Design,
Data Storage and Operations,
Data Security,
Data Integrations and Interoperability,
Document and Content Management
Data Warehousing and Business Intelligence,
Reference and Master Data,
Metadata,
Data Quality.’

DMBok Edition 2

All of these are words, and to the uninitated, can seem a little intimidating. So let me do, what I do best and break it down for you. Data Governance is a lot like exercise. Needed but boring. Done well, you stay healthy and are able to continue well into your later life. Done badly, and you end up with pain and lifelong injuries that you just need to continuously work around until it becomes an insurmountable problem requiring drastic intervention. This doesn’t mean, you won’t get injuries when healthy, but you find the right support and rehab and you’re back on track. If that analogy doesn’t make Data Governance palpable, then click away, because these metaphors are only going to continue! Piqued your interest? Then let me show you how to approach this.

A while ago, I discussed my personal framework. If there is one thing I am a big fan of, it’s having frameworks and guidelines to “teach a man to fish” than to “give a man a fish”.

There are some fundamentals to Data Governance and overall Data Management. Having done it successfully (and failed miserably in some – but that’s where true learning comes in) in multiple organisations, I thought I’d document the “what to do” for everyone’s interest.

These fundamentals are:

• Where we store data
• How we classify data
• Defined Roles and Responsibilities for data ownership
• How long we store data for (retention)
• Who has access to the data
• How do we correct data (data quality and integrity)
• How do we get the best insights from our data
• How do we demonstrate these wins (KPIs are key)

And all of the above require:

• Clearly Defined Objectives
• A common language (aka a Business Glossary)
• Building a business case for Data Governance
• Defining Policies and Standards
  • A data dictionary (standards around fields and what they contain)
  • Metadata (data about data – technical [what does a field mean], business [what function within the organisation does this support] and operational [how long a process ran]). This enables the authorised users to find these assets.
  • High Level Architecture diagrams (what is the golden record and how does it all interconnect for major data flows)
  • Classification of the data assets
  • Storage based on the classifications.
  • Access based controls
  • Data Quality
  • Auditing
  • Privacy Law Compliance
• Lean Implementation and capitalising on wins and repeating iteratively
  • Implementing tools to assist (depending on the size of the organisation)
  • Sales, Marketing and Presentations
  • Change Management and how to influence culture
  • Scaling the Framework
• And finally monitor and refine the overall program
• Added Skills not often spoken about
  • Business Analysis
  • Use Case Development
  • Communication

“Nigel, surely you can’t be serious?! You’re asking for a lot!”
I’m here to tell you, that no, it’s not. And, that you can do it, without upending too many existing processes.
Yes, there will be an increase to people’s workloads, but when done right, it can be a slight increase to many people when executed in a targeted way. (Read non-invasive governance on how to do this!)
At the same time, I will be covering a couple of items that you can avoid and how to scale!

This is the start of a series of posts on this topic. I’m challenging myself to be condense with a topic that I can wax lyrical. I only have 2 goals for my readers for this series:
1. You’re a dabbling in data and want to understand why getting the fundamentals right is important. (Heck, you want to know what the fundamentals are…)
2. You’re about to hire some consultants to do this work for you or even about to write a job description. You can use this to test the knowledge of your applicants. People can say the right things but poke a little deeper and it all comes undone. My aim is to give you enough knowledge to know the difference.

If you need help with implementing your Data Governance Program beyond the above playbook, feel free to drop me an email and I will get back to you on your query.