Every business is inundated with data from every angle. There is pressure to use insights we glean from the data to improve business performance. As a result of this incredible amount of data to process and new tech that helps non-technical people make sense of the data, there is desire and demand for data democratisation. Let's explain what that means, the pros/cons of data democratisation and the tech innovation that has transpired to support this effort.
Data democratisation means that everybody has access to data and there are no gatekeepers that create a bottleneck at the gateway to the data. It requires that we accompany the access with an easy way for people to understand the data so that they can use it to expedite decision-making and uncover opportunities for an organisation. The goal is to have anybody use data at any time to make decisions with no barriers to access or understanding.
Until recently, data was "owned" by IT departments. Business units such as marketing, business analysts and executives used the data to make business decisions, but they always had to go through the IT department to get the data. This is the way it's been for the better part of five decades and there are still some who believe it should remain that way.
Why should there be data democratisation?
Proponents of data democratisation believe it's imperative to distribute information across all working teams to gain a competitive advantage. The more people with diverse expertise who have the ability to access the data easily and quickly will enable your organisation to identify and take action on critical business insights. There are many professionals who believe data democratisation is a game changer. When you allow data access to any tier of your company, it empowers individuals at all levels of ownership and responsibility to use the data in their decision making.
There is still concern by some organisations that misinterpretation of the data by non-technical employees could occur and these employees would then make bad decisions based on their bad interpretation of the data. In addition, the more users who have access to the data the bigger the data security risk and the more challenges to maintaining the data integrity. Some data still exists in silos; although there has been a great improvement in recent years, this reality can still make it difficult for people in different departments to access data and view it. Another concern about data democratisation is a duplication of effort across different teams that could be more costly than a centralised analysis group.
Data virtualisation software: Data virtualisation software retrieves and manipulates data without knowing the technical details about it. This helps avoid the issue of needing to clean up inconsistencies in data or different file formats.
Data federation software: This software uses metadata to aggregate data from a variety of sources into a virtual database.
Cloud storage: One of the ways organisations are avoiding the data silos that prevented data democratisation in the past is by using cloud storage as a central location to store data. Database management security features encrypt or mask data to heighten security.
Self-service BI applications: These applications make it easier for non-technical users to interpret data analysis. We can now have a machine look at data and explain it to non-technical users.
Any organisation who democratises data needs to have strong governance in place to ensure the data is carefully managed. Everyone in the organisation should be properly training on how to best use the data to drive company initiatives and progress. Expect that data democratisation is an evolution where each individual small win when non-technical users gain insight because of accessing the data adds up to ultimately prove the merits of data democratisation.
While it's still too soon to know the full impact full data democratisation across all enterprises, there's still widespread hope that it will revolutionise our business decision-making by allowing employees at all levels to gain access to and insights from the data their organisations collect.