More and more people are beginning to embrace the concept of self-service analytics, and interest in data discovery has grown significantly as a result. According to a recent study, the number of users, consultants and vendors using data discovery and visualization increased from 40 percent in 2012 to 58 percent in 2016. What’s more, researchers found that an estimated 80 percent of the market will depend on BI tools for data discovery over the next three to five years. This increase in interest has led to new demands on data sources, data discovery and training and governance.
New Data Sources
As self-service business intelligence tools grow in popularity, new BI tools have created new concerns for IT professionals, according to a recent Gartner Magic Quadrant report. Newer, less-experienced users are beginning to use BI tools on a regular basis and are seeking more flexibility for data discovery and input. While this has made BI’s insights available to more users on demand, it has also created challenges due to data inconsistencies and manipulation. Last year, it was estimated that less than 10 percent of self-service BI initiatives would be governed sufficiently to avoid inconsistencies in data. This has driven greater discussion around governance between users and IT/BI teams.
Smart Data Discovery
One of the common barriers to self-service BI is that users often don’t know where to access data. Smart data discovery can help mitigate this challenge. Gartner estimates that by 2021, those who use modern BI and analytics platforms with smart data discovery will grow at twice the rate and deliver twice the business value as those who do not. The benefits of this shift towards AI-driven data discovery are many – including automation of analysis, faster data preparation and the uncovering of hidden insights while avoiding the possibility of human bias.
Training and Governance
Smart data discovery and self-service BI go hand in hand, as smart data discovery empowers self-service users get to the right data. On certain platforms, communities can work together to curate data. Yet, there is a caveat -- self-service tools do not teach users how to model data. Most organizations will need guidance to educate their users on how to extract the right conclusions and take the best course of action. Organizations that adopt self-service BI must also adopt ongoing governance that defines roles, responsibilities and processes, and they must support their teams with the right training to ensure best practices are used. Tools that encourage collaboration and allow for commenting and cataloging from users can also empower better modeling and decision-making from business intelligence data.
ProKarma’s approach to BI and data discovery centers on creating a trusted data platform built with timely, reliable data. When combined with intuitive consumption and proper governance, this ensures that employees have the knowledge and tools necessary to make the correct decisions and move forward strategically. Learn more about how ProKarma’s analytics practice helps businesses thrive by becoming data-driven.