Data Discovery

Data Discovery as the Top Business Intelligence Trend

Over the last couple of years, data has become the lifeblood of many organizations. And the usage of modern Business Intelligence became the new norm. As any other technology-driven process, business intelligence sees its own trends. According to BARC’s survey, there are three fundamental trends in the work of BI practitioners: data discovery/visualization, data quality/master data management and self-service BI.

We are about to take a closer look at Data Discovery and find out what stands behind this fashionable term.

Data Discovery

Named one of the key business intelligence and data analytics topics according to BARC’s Business Intelligence Trend Monitor 2018 study, data discovery has been around for a while now, almost two years in a row. The study results reveal the increasing adoption and perceived value of data discovery tools by BI practitioners and consultants, as well as by business users around the world.

So what does it really have to offer?

Put simply, data discovery is a process by which users identify interesting data patterns and values through exploring and inspecting data with the help of visual methods. However, it is not a one-off action, but a continuous process that consists of three integral parts: data preparation, visual analysis and guided advanced analytics.

The level of investment in this area is incredibly high. BI vendors and customers are all placing their bets on the future of data discovery. No wonder why: going beyond traditional reporting and performance tracking functions, this new data-driven approach makes it possible to exploit all the benefits of the data asset.

Although data discovery can be carried out without the need of sophisticated statistical modeling and hypothesis checking, it still requires certain analytical skills to identify data patterns and extract useful information out of it.

However, there are a number of data discovery tools available in the market designed to ensure seamless integration of data preparation, visual analysis and analytics. Most of these tools can access and handle big data sets from multiple data sources and offer comprehensible visual techniques for data representation.

How NLP Supports the Data Discovery Process

What all these tools have in common is that they target business users and provide a code-free environment for data discovery. In other words, users don’t need to learn programming languages to be able to make sense of the data they receive.

Natural Language Processing plays a huge role in this process. Applying NLP to BI tools makes it possible for non-technical people to analyze data themselves, instead of having to wait for their IT analysts to run complex reports. In other words, thanks to NLP, everyone involved in the business process can have full and timely access to information in order to be able to make informed decisions.

The promises of NLP-powered BI solutions are truly amazing. Natural Language APIs - like FriendlyData - will help your business maximize the benefits of BI by turning them into fantastic business productivity.