While CIOs and CDOs realise that simple data management allows organisations to generate insights from their data, they cannot be sure whether this data is accurate, relevant or where it originates from. It is therefore questionable whether conclusions drawn from this data are of any real value to the business.

Data governance ensures that the right people are involved at every step of the data management process – making decisions, understanding impact, supplying context, prioritising deliveries, and staying informed. An appropriate data governance framework – that can be tailored based on your organisation’s maturity, business needs and priorities – ensures a structured approach to meeting your data management goals, now, and in the future.

Still difficult to find an appropriate framework?

“Finding an appropriate data governance framework can be difficult. Many of the available frameworks are too specific, created for a distinct vertical and specified company requirements that may not match those of your organisation; while others are too broad, generic, or high-level, making, it tough to relate back to the business or specific use case,” says Kerry Allemann, Senior Consultant at Master Data Management (MDM).

MDM, a provider of complete data management solutions, recently announced its latest industry-agnostic and adaptable data governance framework, which can be tailored according to an organisation’s specific business requirements. The implementation is a change management process that considers the organisation’s goals, data strategy and culture, in addition to its data governance and management maturity level.

This approach to data governance comes at a time when organisations are increasingly recognising the need for data management and governance. The need is largely driven by legislation such as the Protection of Personal Information Act (PoPIA), as well as the realisation that data has value and can yield increased earnings when used correctly in the digital age.

“With a customised governance framework in place, organisations can increase their levels of efficiency and improve their data management practices. Improved practices allow companies to know what data they have and where it is stored, thus also enabling them to identify duplicates, consolidate information, and streamline processes,” says Allemann.

Working with an experienced partner, like Master Data Management, allows organisations to tweak the framework according to their immediate need, phasing in additional complexity later.

For example, a company that is focussed on delivering self-service business intelligence may begin by putting controls in place enable data scientists and other knowledge workers to find and access the data sets they need to do their jobs, whilst an implementation focused on the Protection of Personal Information (POPIA) has the opposite goal – that of ensuring access to sensitive data is restricted. A data governance framework, supported by an experienced partner, must provide the road map to deliver either goal, but eventually cater for both.

Good business practice

“Improved data management practices not only equate to good business practice, but also facilitate regulatory compliance, by allowing companies to control access to and modification of their data.”

Most organisations find it difficult to successfully implement a data governance framework, which prompted MDM to take a collaborative approach, working hand-in-hand with the client to identify priorities and plan implementation accordingly.

“We jointly identify a particular starting point, based on a broader picture that includes the client’s data strategy, culture and current levels of maturity. Once this is established, we collaboratively implement the governance framework, adapting it to your specific requirements,” says Allemann.

“We have incorporated our nearly fifteen years of data governance implementation experience into our new framework, which has now been added to our growing offering. This includes our Enterprise Information Management framework (EIM), PoPIA implementation framework and MDM implementation framework, to mention a few.”

Alleman notes that MDM’s enterprise approach engages stakeholders, across business and IT, to share knowledge, minimise unwanted impacts and build trusted data within an organisation.

“Companies that practise active data governance – embedding data stewardship and curatorship activities into business-as-usual data processes – report significant advantages in their ability to use data effectively,” she concludes.

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