In They say that the insights from a BI engine will be only as good as the quality of data that is fed in it. While there's no denying the validity of this argument, given the tremendous growth in the number of data sources in the recent years, it can be now be said that the insights from a BI engine will be only as good as the variety of data sources it refers to.
Research and advisory firm Gartner has urged BI and analytics professionals to consider the robust growth in the number of data sources when embarking on any initiative. It feels that business intelligence leaders must embrace a broadening range of information assets to help their organizations. The firm has even outlined three key predictions for BI teams to consider when planning for the future:
By 2015, 65 percent of packaged analytic applications with advanced analytics will come embedded with Hadoop. Organizations realize the strength that Hadoop-powered analysis brings to big data programs, particularly for analyzing poorly structured data, text, behavior analysis and time-based queries. While IT organizations conduct trials over the next few years, especially with Hadoop-enabled database management system (DBMS) products and appliances, application providers will go one step further and embed purpose-built, Hadoop-based analysis functions within packaged applications. The trend is most noticeable so far with cloud-based packaged application offerings, and this will continue.
By 2016, 70 percent of leading BI vendors will have incorporated natural-language and spoken-word capabilities. BI and analytics vendors continue to be slow in providing language- and voice-enabled applications. In their rush to port their applications to mobile and tablet devices, BI vendors have tended to focus only on adapting their traditional BI point-and-click and drag-and-drop user interfaces to touch-based interfaces. Over the next few years, BI vendors are expected to start playing a quick game of catch-up with the virtual personal assistant market. Initially, BI vendors will enable basic voice commands for their standard interfaces, followed by natural language processing of spoken or text input into SQL queries. Ultimately, "personal analytic assistants" will emerge that understand user context, offer two-way dialogue, and (ideally) maintain a conversational thread.
By 2015, more than 30 percent of analytics projects will deliver insights based on structured and unstructured data. Business analytics have largely been focused on tools, technologies and approaches for accessing, managing, storing, modeling and optimizing for analysis of structured data. This is changing as organizations strive to gain insights from new and diverse data sources. The potential business value of harnessing and acting upon insights from these new and previously untapped sources of data, coupled with the significant market hype around big data, has fueled new product development to deal with a data variety across existing information management stack vendors and has spurred the entry of a flood of new approaches for relating, correlating, managing, storing and finding insights in varied data.
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