According to Gartner Inc., business intelligence (BI) and analytics need to scale up to support the robust growth in data sources.

Gartner has pit forward three key predictions for BI teams to consider when planning for future requirements:

By 2015, 65 percent of packaged analytic applications with advanced analytics will come embedded with Hadoop.

Organisations realise the strength that Hadoop-powered analysis brings to big data programs, particularly for analysing poorly structured data, text, behavior analysis and time-based queries. While IT organisations 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.

Moreover, Gartner says that by 2016, 70 percent of leading BI vendors will have incorporated natural-language and spoken-word capabilities. Currently, BI or 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.

Also, the firm says that 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 optimising for analysis of structured data. This is changing as organisations 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.