Data democratization is a craze that’s not going away any time soon. More and more companies are trying to give their employees access to data to help them improve job performance and overall company health, but with this has come specific challenges.
One of these has been simply that with the hunger for data from all areas of the company, trying to keep up with this demand has become a real struggle for data teams, especially when understanding of data throughout the company demands more complex analysis. This has created a conundrum for many companies - they want to give each employee the chance to be data-driven, but they lack the resources to deliver.
One of the big developments we have seen to try and solve this problem has been the emergence of self service analytics. The idea behind this is that it allows everybody in the company to essentially become a data scientist, by making data available to whoever wants it, whenever they want it. This is most commonly done through dashboarding, which can show real-time data, but in some cases can also be fully implemented analysis tools.
It is big business too, with companies like Qlik having seen over $700 million in sales. They now sit at number 10 on the Forbes Innovative Growth Companies List. The key to their success has been in making the complicated simple. Their CEO Lars Björk pointed out the pride the company had in this fact during an interview with Forbes, ‘I think we can take pride in the fact that we were the ones that introduced the whole notion of (BI) self-service and making this something very easy to use. So simple my mother can use it.’
It is therefore no surprise that some have labelled self service analytics as the great democratizer, but is it a justified title?
As Björk told Forbes, ‘Coming into the market, we took the approach that every user could be a little bit of a data scientist.’ Qlik essentially took a UX approach to data science, something that hadn’t really been attempted before. It certainly allowed more employees to be able to interact directly with data and there have been significant positive reactions to the move.
However, it may not necessarily be a totally positive move and in some cases has led to a decline in the quality of analysis. Jon Pilkington, chief product officer at Datawatch points out in an article on Smart Data Collective that although many companies give employees access to data, it is still often hard to find. Even when it is in a centralized location, with so many people having the opportunity to change datasets, store pre or post analysis or even just name files in non-standard ways, makes it difficult for employees to utilize it effectively. According to Jon, ‘Not only does this cause analysts to make valuable business decisions based on incomplete information, but it also forces them to work in seclusion.’ This is clearly not ideal for the concept of data democratization.
So although self service analytics are certainly having an impact on data democratization, there is more to be done in order to maximize their value. It is not enough to put the technology in place, it is essentially to have the infrastructure in place behind it to make it work, plus the training necessary for staff to bring real value.