3 predictions BI teams should consider when future planning
Today, organizations are exploring and combining insights from their vast internal repositories of content, including text and emails and (increasingly) video and audio. Additionally, they are also tapping externally generated content such as the exploding volume of social media, video feeds, and others, into existing and new analytic processes and use cases. Correlating, analyzing, presenting and embedding insights from structured and unstructured information together enables organizations to better personalize the customer experience and exploit new opportunities for growth, efficiencies, differentiation, innovation and even new business models.
So it is not surprising that Business intelligence (BI) and analytics need to scale up to support the robust growth in data sources, According to the latest predictions from Gartner, business intelligence leaders must embrace a broadening range of information assets to help their organizations. The three key predictions for BI teams to consider when planning for the future are:
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.
“Organizations with the people and processes to benefit from new insights will gain a competitive advantage as having the technology packaged reduces operational costs and IT skills requirements, and speeds up the time to value,” said Bill Gassman, research director at Gartner. “Technology providers will benefit by offering a more competitive product that delivers task-specific analytics directly to the intended role, and avoids a competitive situation with internally developed resources.”
By 2016, 70 percent of leading BI vendors will have incorporated natural-language and spoken-word capabilities.
BI/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.
“Many of these technologies can and will underpin these voice-enabled analytic capabilities, rather than BI vendors or enterprises themselves developing them outright,” said Douglas Laney, research vice president at Gartner.”
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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