- The ‘democratization of analytics,’ essentially getting analytics tools and insights into the hands of the masses, is the next step forward in a world eager to leverage greater business intelligence.
- Tableau is taking on the challenge by providing tools such as Explain Data and Ask Data, which are designed to make it easier for line-of-business users to extract insights from their data visualizations.
There is no doubt that the vast amounts of data being generated today contain a wealth of valuable information. But, unlocking the strategic insights contained within this treasure trove of material remains elusive to many. Sure, data scientists and data programmers have the tools to perform the analysis at their fingertips, but their techniques remain out of reach to many line-of-business users. Extracting insights from data and getting it into the hands of those outside of the IT department is a challenge. The ‘democratization of analytics,’ essentially getting analytics tools and insights into the hands of the masses, is the next step forward in a world eager to leverage greater business intelligence.
Tableau is eager to take on the challenge of greater ‘democratization of analytics.’ With a legacy built on providing software that makes data easier to understand via improved visualization, the company is well positioned to deliver tools that make it more intuitive to extract insights embedded within large volumes of information. At its TC19 customer conference in Las Vegas, Tableau underscored the need for all organizations to embrace a culture of data, one in which the use of analytics by all knowledge workers becomes ubiquitous.
To enable access to data analytics by a broader audience, Tableau has rolled out several new capabilities. Explain Data, which was made generally available in the latest 2019.3 software release, is designed to provide faster and easier discovery of insights. It helps non-data scientists progress from seeing only what happened to understanding why it happened. The tool uses AI-driven statistical algorithms to analyze available information and automatically generate relevant explanations for a data point. After a user selects a field within a visualization for which he or she would like to perform deeper analysis, Tableau evaluates patterns and potential explanations, providing the most relevant and statistically significant results. By empowering users with the ability to better understand their data, as well as changes in their data, Tableau expects them to be better positioned to act on the information.
Similarly, Tableau’s Ask Data feature is designed to make interacting with data more intuitive. The AI-driven tool uses natural language processing (NLP) to understand user requests, enabling access to analytics via an easy-to-use interface. Ask Data intelligently parses queries to resolve ambiguities and understand semantics. With the latest 2019.3 release, Ask Data can be embedded into company portals or intranet pages, allowing more people to verbally interact with data. By using only spoken questions, users can pull information from the software and request different data views and tables.
Initiatives that enhance access to valuable insights by a broader audience go a long way in building a data-driven corporate culture. But, while these efforts will promote the ‘democratization of analytics,’ the business world is only scratching the surface of ubiquitous analytics. Standing in its way are numerous concerns, such as those related to explainable AI, trust in data, and data governance. Users will only be willing to take action on analytical insights if they understand how findings were obtained, if they have confidence in the quality and source of the data being used in the analysis, and if they have access to appropriate and relevant information, which requires a well-developed data management policy. Making data and analytics easy to use and readily available is a first step in a long journey. However, while the road ahead may be slow and winding, the benefits to be reaped along the way are readily apparent to all.