Data mismanagement is an issue affecting businesses across the globe – and with the amount of data being created, stored and shared, it’s no wonder that we are experiencing such an epidemic. 

The high volume of poorly managed data doesn’t just prevent companies from effectively leveraging information for business intelligence. It results in many other damaging factors such as poor decision making, increased compliance risk, tarnished reputation and a loss of customers and opportunities. The cumulative impact and costs of which can cause a lot of harm (in some cases, irreparable) to a business. Data is such an invaluable asset – one that companies simply can’t afford to mishandle. 

The proper use and management of data presents businesses with an opportunity to make better, well-informed decisions which ultimately lead to increased revenue and promotes growth.

What is Data Governance?

Data governance forms the basis for company-wide data management. It includes the people, processes and technologies that are needed to manage and protect a business’ data assets. This helps to guarantee corporate data that is understandable, correct, complete, trustworthy, secure and discoverable. It covers: 

  • Data quality. 
  • Data architecture. 
  • Data modelling and design. 
  • Data storage and operations. 
  • Data security.
  • Data integration and interoperability. 
  • Documents and content. 
  • Reference and master data. 
  • Data warehousing and business intelligence. 
  • Meta-data. 

Fundamentally, data governance establishes methods that allow a company with clear responsibilities and processes to standardise, integrate, protect and store corporate data; the key goals of which being to:

  • Minimise risks. 
  • Establish internal rules for data use. 
  • Implement compliance requirements. 
  • Improve both internal and external communications. 
  • Increase the value of data. 
  • Facilitate the administration of the above. 
  • Reduce costs. 
  • Help to ensure the continued existence of the company through risk management and optimisation. 

What’s the Benefit of Introducing Data Governance on a Company-Wide Level? 

Company-wide data governance is fundamental to a company’s data management success as it:

  • Delivers greater visibility into data assets. 
  • Strengthens a business’ accountability for their data. 
  • Enables better utilisation of a company’s data. 

While a lot of companies already have data governance initiatives in place, their efforts generally tend to be isolated to specific areas, departments and focused policies. The trouble with this is that in today’s fastpaced and ever-evolving world of innovation and automation, this siloed method of data governance isn’t working the way it needs to. 

Businesses require a company-wide data governance strategy designed with business users in mind in order to encourage a data-driven culture built on data understanding and collaboration. 

How to Implement Data Governance Throughout your Company

Before you get started, you need to establish a team of people who will be responsible for overseeing your data governance efforts. 

Appoint a data governance leader – Appoint a data governance leader – usually the Chief Data Officer (CDO). The CDO will oversee the entire team and ensure that critical data governance tasks remain on track on a business-wide level. 

Appoint team leaders – The leadership of data governance shouldn’t stop at just a data governance leader. The next step should be to appoint leaders from teams across the company. This might include finance, marketing, HR and IT, for example. These people, along with the CDO, should be responsible for developing data governance policies and procedures and manage the administration and adherence of these rules.

Build a team – Once you have established your data governance team, you should bring together a team that represents all areas of your business. Their job will be to manage the essential components of your data governance program. The responsibilities of this team will include: 

  • Establishing common data definitions and data glossary. 
  • Developing a data catalogue and determining what should be included. 
  • Creating metrics as well as data quality scoring and monitoring. 
  • Clearly defining roles and responsibilities among data owners, business users and stewards. 

Data Owners

It’s the data owners’ job to ensure the continued regulatory compliance, appropriate access, usage and quality of their assigned data assets. They hold responsibility for the data as it flows through the company’s data supply chain and oversee the correct usage of the data in accordance with the company’s defined policies and procedures. 

Data Stewards

Data stewards are responsible for interpreting data sets, producing reports and responding to questions from business users. 

Business Users

Business users must follow all established policies and procedures outlined by management and report any data anomalies to the data owners.

Having such clearly defined roles and responsibilities, the whole team becomes engaged and you begin to endorse a collaborative culture amongst your staff. 

Adopting Modern Technologies

Establishing a data governance team is a great first step towards fostering a data governance program. However, there is still more road to cover if you want your efforts in doing so to prove effective and worthwhile. Your team will need the right resources if they are going to fulfil their data governance duties.

Successful data governance requires a comprehensive strategy. To facilitate an effective data governance framework your data governance team will need to implement an enterprise data intelligence platform that can deliver a broad range of integrated features for data governance, data quality and analytics. This platform must: 

  • Offer complete transparency into your company’s data landscape. 
  • Enable all users to easily define, track and manage all aspects of your data assets. 
  • Encourage a community approach to data management which brings people and data together. 
  • Clearly define ownership and accountability for all high-value data assets to ensure that business users know who to go to with any questions that they might have regarding their data. 
  • Include data quality capabilities to ensure data remains complete, accurate, relevant and consistent across the data supply chain to ensure business users have the confidence to utilise all of the data assets available. 
  • Hold analytics capabilities with machine learning algorithms that can monitor data quality which will help to maximise your data governance efforts and, in turn, enable you to improve data integrity automatically. 

We have put together a whitepaper on how to create a business case for data governance which you can download for FREE.

Download Now >