Ovum forecasts the business intelligence (BI) and analytics market to reach $27bn in 2021, with self-service analytics powering much of the new adoption over the next five years. Our view of the fundamental drivers to enterprise adoption of self-serve analytics (data discovery, ease of use, and simple deployments) remain unchanged because they enable faster data-supported decision-making for more of the enterprise. If the drivers are the same, however, how can the vendors differentiate themselves? Offering ever more "human-friendly" solutions to eliminate the barriers to adoption appears to be the method employed by the majority of vendors. Our research reveals that, while no one vendor dominates the self-service analytics market, the race to do so is on.
Our 2017 self-service analytics market landscape report recognizes two broad types of pressure guiding vendors' investments in their solutions' development. First, self-service vendors are offering increasingly similar features; this market convergence means that vendors must innovate to differentiate themselves. Secondly, other enterprise application vendors are baking analytics capabilities into their platforms. Today, self-service analytics capabilities are still more advanced than any of the analytics tools currently built in to enterprise applications, such as customer relationship management and enterprise resource planning; however, investing in new capabilities, and the way users interact with them, is the best way for pure-play analytics vendors to stay ahead.
Our research suggests that in order to meet the evolving analytics requirements of enterprises, vendors must focus their investments on developing a "human UI." Over the next five years, users expect to visualize increasing amounts of information without being inhibited by analytics platforms' growing technical complexity. To address this demand, vendors should invest in natural language processing, user journey prediction, and automated predictive data analysis. These features are the essential building blocks of the intuitive, visual UI that will allow nonexperts to perform complex analytical operations without needing to code.
This "human interface" should also be extended to incorporate data-cleansing tools to help users easily manage a growing data load. Self-service analytics vendors are beginning to offer a greater range of data preparation tools to help users obtain the right data set to conduct their analyses. Ovum argues that in the future, vendors should perfect their transformation tools by making them more human friendly. This includes performing data joins, column detection, and semantic standardization using natural language and visual drag and drop within the self-service analytics solution. Alongside this automation, the solution should be able to offer useful insights into the data, helping ensure its validity for use. Our market landscape report concludes that, among the 18 vendors reviewed, those able to deliver human-friendly solutions will be best positioned for the future of analytics.
Market Landscape: Self-Service Analytics, 2017, IT0014-003293 (June 2017)
Laurent Lioté, Analyst, Information Management
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