By IT Support Team on Monday, 17 August 2020
Category: Insights

Data Democratisation - What is It and Why is It Important?

In this Information Age, businesses have been inundated with all types of data from various sources—social, machine, and transactional data. Despite the rapidly growing flood of big data however, access to information primarily remains with those who have the technical capability to analyse the data.

Now, as more organisations realise the power of data to transform a business, many have recognised the need to make data more accessible to others. Hence, the conversation on data democratisation. In this post, we discuss what it is and why it could be beneficial to your business, why access to data was previously limited to a select few, and what you can do to implement a data democratisation strategy that equally addresses both risks and benefits.

Data democratisation defined

With its name implying the application of democratic principles, data democratisation is the process by which data is made accessible to everyone. This means that even the average, non-technical user can retrieve and interpret data at any time.

The perennial need to keep data secure has compelled enterprises to ensure that any important information is only made available through IT departments, which have created bottlenecks at the gateway to data pools. But these can all change once data democratisation is implemented in more businesses.

The advantages: Why it’s beneficial for organisations

Having the capability to distribute data across all departments is a huge benefit for any company and gives them a significant advantage over their competition. This is because easier access to data also leads to timely and critical business insights that are the foundation of every informed decision. Thus, data democratisation ensures that no time is wasted when it comes to implementing crucial strategies and making business decisions.

In addition, with a data democratisation policy in place, all company employees, regardless of expertise and technical skill, can have access to the data they need when they need it. This empowers them to use the data and gain better perspective in decision making, whether individual or collective. It also helps establish data reporting and analysis as part of day-to-day operations, thus encouraging a data-driven culture within the organisation.

The disadvantages: Evaluating the downsides

Data sharing, and consequently data democratisation, has been met with apprehension by many pundits; and for good reasons. One valid argument is data security. The more individuals with access to it, the greater the risk of compromise and the potential threat of a data breach. That’s why traditionally only a handful of people were given unlimited access to data: mainly data scientists and analysts, IT professionals, and C-suite executives.

The high probability for misinterpretation and/or misrepresentation of data is another major cause for concern. Employees who have not been trained to analyse data properly may tend to interpret data erroneously, resulting in unsound decisions and possibly huge financial losses to the company.

Having a well-thought out data democratisation strategy may sound well and good, but it does come with a hefty price tag. There are various factors to consider—from establishing the legal framework for the implementation, to getting the right tools and technology to enable enterprise-wide accessibility, to ensuring data security at all levels, and more. These all require the company to invest considerable resources into this large-scale project.

Best practices for data democratisation

Organisations that intend to benefit from data democratisation need to come up with a sound strategy for its implementation. Here are three important steps that should be integrated into any plan:

Data democratisation is the answer to maximising the value of big data. And with the availability of tools and technology today, enterprises are able to rethink the way they manage and distribute data, allowing more employees to make smart, data-driven decisions.

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