Data Democratisation: Broadening the Reach of Data for the Business

Even though data has become the lifeblood of every organisation, it is still not accessible (or even understandable) to all employees.

The potential of data is virtually limitless. It can be used to transform, enrich, and boost companies by harnessing the value of the information they have at their disposal. To do so, however, requires decision-makers to embrace the concept of ‘data democratisation’.

Data democratisation can be defined as the process of making digital information accessible to the average non-technical user of information systems, without having to require the involvement of IT. Sounds straightforward. In practice, it requires organisations to navigate the complexities of their data real estate and find more effective ways of promoting collaboration between data creators and data consumers.

Using business intelligence solutions and, more recently, automated analytics driven by artificial intelligence and machine learning is considered by many to be the silver bullet required to affect this change. But it is not only a technology problem that needs fixing but a human one as well.

Understanding Data

The journey begins with employees improving their critical thinking skills as these relate to data. This does not mean every worker should become a data scientist. Instead, it is about people becoming comfortable enough with the data to ask relevant questions to unlock more value.

Underpinning this people-centric change is ensuring the organisation has a solid foundation in place for a democratised data approach.

The traditional siloed approach of the past can no longer be considered adequate. It is an organisational-wide requirement that must transcend individual departments. A long-term investment in integrating the data relationships across business units is fundamental.

There is a need to track data through its lifecycle – from its creation to the endpoint of the decision process. Clearly, this is not something that can happen overnight but requires a long-term investment that will fundamentally shift the business to become a data-driven one.

Dealing with Scale

The sheer volume of data being generated at the edge, across digital channels, and user platforms, are making it impossible for human resources to effectively manage and analyse.

This requires the injection of machine learning and automation technologies capable of dealing with data at scale. However, these more advanced solutions will not replace human specialists. The technologies will enhance what human operators can do and eliminate any bottlenecks in analysing data.

Again, this is where an expanding user skill set becomes vital. If employees do not understand how machine learning, automation, business intelligence, and other solutions work, then they will not be able to capitalise on the insights that can potentially be generated.

By combining advanced technologies with more aware users, companies can start shifting to becoming an agile environment. Even so, data democratisation requires data to be readily available. As such, companies need to adopt modern and relevant architectures that can be deployed in rapidly emerging cloud environments.

Ongoing Management

Ultimately, effective data democratisation that factors all this and more is something that is continuous. Companies cannot simply transform and think they are over and done with the process. User awareness training, upskilling, and reskilling are all core components of this.

Building comfort levels is one thing. But taking that and maintaining it over the long-term is where the real challenge comes in. Also, there is no universal approach to democratising data. Each organisation is unique and its needs are different. Building a data democracy will take work and commitment by all.

By Jessie Rudd, Technical Business Analyst, PBT Group.

Edited by Zintle Nkohla

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