What is data democratisation and why is it necessary?
Jadd Elliot Dib is the founder and CEO of UAE-based Pangaea X, an online network and talent acquisition platform for data analysts
It is about time to reveal that the financial truth of any organisation today is in data. Companies use data analytics to help improve business performance, plan better, deliver an enhanced customer service experience and make better decisions, although data analytics can still be very overwhelming for non-technical employees in organisations.
First, it’s important to discuss data democratisation. This is when data is available and accessible to everyone across a business. The objective is to make data available for everyone, so they can make better and more expedited decisions leading to more business prospects.
Why is it beneficial to have data democratised?
Data democratisation makes it easier to process big data for people who do not have technical skills, yet want to use data in order to achieve better results and make everyday life easier. One way to do this is by using data virtualisation software, which retrieves and manipulates data without knowing its technicality. This can help individuals read data without cleaning up any data inconsistencies. The other common way is through cloud storage which provides encrypted security that prevents any security threat to the data. Another way is to use self-service business intelligence applications that are designed to retrieve, analyse, transform and report data for business intelligence, making data analysis easier for non-technical people.
What are the different steps to consider when getting started with data democratisation?
Every organisation should be aware of their business and where data mining can happen. Before any further steps, it is crucial to have a clear understanding of the goals and how to achieve them. Companies must be aware of each department’s strengths and weaknesses. Then the performance of every team and individual can be tracked. When data is made available to employees, they are better equipped to identify any leaks, challenges, or room for improvement in their respective tasks.
The objective of data democratisation is that it should be easily understood by everyone. If the data is not organised clearly, then the whole purpose is defeated. Unclear information will lead to misleading analysis and ultimately to poor decision making. Thus organisations need to clean the data and fix structural errors before connecting it with analytics.
Before access is granted to utilising the data, companies need to make sure that the importance and the processes are well understood. Hence it is crucial to invest in training for individuals to interpret data accurately.
We are witnessing some rapid advancements in artificial intelligence (AI) and machine learning (ML), which makes analysing data easier than ever. ML is a group of techologies that allow computers to learn from data. A great example is Airbnb – they made use of data science and ML in their technology. In 2017 its data science team consisted of nearly 100 people. The company’s core belief is that everyone should be empowered to use data when making a decision and very smartly split up its efforts into data education, data access, and data tools. There are several more great examples, like Kaggle, a machine learning competition company owned by Google that offers free-to-enter ML competitions, where people can find all the code and data for their data science work.
But if data is democratised across the board, there must certainly be implications around it. Any company who decides to make data accessible to everyone should be backed up by strong governance, so data is managed carefully. Obviously data democratisation cannot be applicable across all entities, for example governments cannot democratise data to all employees as it would have serious repercussions on classified information.
Companies are still concerned about the misinterpretation of data by non-technical people that may lead to poor decisions. In addition, the increased number of users can lead to increased data security risk, potentially resulting in security breaches. However, more and more companies believe in data liberalisation to enable and ensure better data-driven decisions.
It is still however too early to know the full impact of data democratisation across all entities, but it will definitely change the way we make business decisions allowing and empowering employees to have full visibility on the data their companies collect and gain insights into areas where they could not before.