Oakland Group

How does traditional Data Governance get ready for Data Mesh? 

Much has been written on the technical changes arising from more and more Data Mesh deployments as organisations seek to achieve a step-change in collecting, organizing, and utilising their data assets. But far less has been written about the non-technical changes that will be needed to achieve such a change in general and Data Governance in particular.

In her latest instalment, Data Mesh Guru, Zhamak Deghani https://www.thoughtworks.com/profiles/z/zhamak-dehghani gives an overview of the significant cultural and organisational change needed to implement a Data Mesh solution effectively. 

This includes the recognition that the current role of Data Governance will need to “shift”, with the caveat that the exact manner of the “shift” will be expected to vary from one organisation to another. 

This undoubtedly will be the case, but we believe it will need to be more than a “shift”. It is much more likely to require a complete rethink in how Data Governance Managers and their teams organise themselves and carry out their roles.  

This will be new news and not necessarily what current Data Governance professionals expect. 

So the sooner the profession starts to face into the changes arising from Data Mesh, the more likely that Data Governance can be part of the solution rather than being an afterthought.

Let’s consider some of the Data Governance activities likely to change.

Data Policies & Frameworks

The effective data governance of Data Mesh will still require the appropriate Data Policy(s) and Data Framework(s). This is good news as this is one of the key tasks to good Data Governance, and this will continue with the adoption of Data Mesh. However, the bad news is that the policies and frameworks will need to significantly change to reflect that those involved will now reside in very different types of teams.  

The more traditional Data Governance command and control approach from a centralised team or individual(s) will simply not work in the same way. Data Governance professionals will need to think about how a data mesh data policy will align across multiple data domains and data structures.     

Data Ownership 

The current best practice approach to data ownership is to create a network of Data Owners, Data Stewards, and Data Custodians. Taking data stewards as an example, currently, these individuals are in charge of managing, investigating, and resolving data issues for one or multiple domains. With data mesh, this role will move to the specific data domains and become part of the domain itself. Therefore, the stewardship role becomes more about being a data product steward.   

People currently in these owner, steward, and custodian-type roles will have a choice to make. Either shift to a domain data product role or become a data platform specialist, assuming such a role exists. This role may no longer be required for data custodians who are usually hands-on and in charge of the day-to-day work with data sources and maintaining the data. 

It could shift to the data mesh domains as a data product developer role, but these are very early days, so it is too soon to be sure.

Also, it is essential to note that in a Data Mesh structure, 

if the roles and responsibilities have been well defined, it begs the question as to whether there will actually be a need for the traditional data ownership model.

Data Artefacts

In the same vein, within Data Mesh, the need for data definitions to ensure consistency across the data domains will be even more important. However, getting such discipline will be more challenging than at present, as Data Governance teams will have to deal with a broader number of stakeholders.

Data Committees & Councils 

The structure within an organisation, which is the highest decision-making body with accountability for data, would change in a Data Mesh world. The representation at such committees and councils would be a federated model with representatives from the respective data mesh domains rather than the more traditional functional areas.

Data C-Suite  

Functional executives, such as the Chief Data Officer or Chief Technology Officer, have been concerned with all things data. They are accountable for the enterprise-wide creation, utilisation, and governance of data that drives business benefit. Moving data from a specialised concern to a generalised one, with the distribution of the data responsibility moving to cross-functional domain teams and the dispersion of data expertise, will change their roles.  

Leading to more of an enablement role, with close collaboration required with fellow C-Suite colleagues.  

Data Literacy

Data mesh requires everyone to have the core skill sets needed to recognise, understand and use data. There will be the need to remove the barriers of organizational silos between the data specialists and everyone else to help ensure the cross-fertilisation of the appropriate data skills. Organisations will need to invest in creating and executing planned data literacy programmes for all levels of staff, including increased data training and new career development pathways to allow people to step into these new roles. It will be even more important that people share data knowledge across the organisation to achieve the common goal of data democratisation.

In Summary, Data Mesh is still at an early stage of evolution. 

However, it will undoubtedly change the way in which Data Governance is designed and delivered. Data Governance professionals have a limited window of opportunity to plan how they will adapt and modify their roles as these changes happen.    

If you’d like to talk to one of our data governance experts on how to integrate data mesh into your organisation then please contact us.