When they first made their debut, concepts such as big data, data management, data governance and data quality were pretty big buzzwords on the data scene. However, as time has progressed, there is much less hype around these terms as they have become a staple part of business vocabulary. 

This is by no means to say that these key topics have lost their importance or impact in the business world, though. In actual fact, properly managed and adequately governed data can help to ensure the accurate and trustworthy delivery of data to business users – and the criticality of this is certainly not lost amongst them.

Not only does data drive virtual business decisions; but it also allows for profitability and growth in organisations regardless of size or industry.

Banks routinely analyse their customers’ income and savings as well as their spending and borrowing habits. This helps them to identify opportunities to offer personalised services, products and communications. Whereas companies in the insurance sector use data to identify potential fraud, opportunities for subrogation and to reduce inefficiencies and costs by shortening claim cycles.

These examples only represent a small constitution of how data is being used across different industries, but companies in all sectors are leveraging their data to:

  • Enhance day-to-day operations.
  • Optimise customer experience.
  • Establish customer loyalty.
  • Enable digital initiatives.
  • Improve business decisions.
  • Increase growth.

With that being said, there are still many businesses who fail to realise maximum value from big data because business users don’t understand how to access and analyse data and apply the insights they generate for strategic decision-making.

Data Evolution for the Business User

Business users are the primary consumers of enterprise data – which is no surprise when you consider that data has filtered into and influences every aspect of an organisation. It’s all in an effort to build a greater understanding of operations and to gain insights to accommodate more strategic decision-making.

Data access requests are growing; they are becoming more and more complex, and it’s all down to the sheer increase of demand on data. Business users need to be empowered to take the lead on data analysis. However, they often struggle to translate technical dialect into business terms. As valuable an asset as data is, it’s only useful if users can actually understand it from a business standpoint and turn it into meaningful insights.

Companies are starting to formally align business users, technology and processes through data governance. The reason is to break through any potential confusion that business users might face when leveraging data. For this reason, users need to assume a more prominent role in enterprise data management.

Fundamentally, data governance is about increasing the understanding of data so that it serves the needs of everyone within an organisation. Having said that, the most successful companies are creating a self-service data governance model that can specifically help business users to find new and creative ways to use data.

Self-Service Data Governance

The goal overall goal of self-service data is to divert attention away from the complexity business users face when searching for and analysing data. Presenting them with an intuitive and simple to use interface is very important, as it allows them to interact with data in a way that is completely tailored to their needs.

When all is said and done, this interaction should imitate something like ‘Amazon Marketplace’ in terms of searching, requesting and accessing the organisation’s data assets – something clear and straightforward to use while leaving no room for any confusion around the data being stored.

When creating self-service data governance, the key is to expand access to data which is driven by built-in security and data quality. This helps business users to serve their own individual needs. By connecting different disciplines into one enterprise-wide initiative, users across all areas of the enterprise can find, sort and analyse data at the touch of a button to gain meaningful insights.

Of course, technology plays a critical role in facilitating the data marketplace as well. Regardless of the solution being used, critical capabilities to ensure success will always include data governance, data quality and analytics. The solution should deliver complete transparency into a company’s data landscape by providing users with a visual drag-and-drop interface to quickly combine data sets, apply pre-packaged data quality checks and analyse data through easy-to-use transformation, blending and machine learning algorithms.

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

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