May 9, 2013 – The potential of business intelligence applications and operations in the cloud has been, to this point, “long on promise,” though changes to how business data is analyzed and accessed are rippling through enterprises from new on-demand capabilities and interest, according to a new report from Saugatuck Technology.

Saugatuck forecasts a big shift to more business intelligence in the cloud in the near future. According to survey results in the report, enterprise preferences for BI will drastically transition from on-premise to some variation of cloud deployment or as-a-service over the next four years. Purely on-premise business software is the preferred path for 50 percent of respondents, though that number dips to 18 percent for 2015 and lower still to 13 percent by 2016, according to Saugatuck’s figures. At the same time, approximately 40-to-60 percent of enterprises will opt for a hybrid on-premise and in the cloud application path from 2014 to 2016. And wholly cloud-based solutions are in the plans for about 10 percent of enterprises as of next year, but that expectation rises to 39 percent by 2016, according to Saugatuck.

Despite projected growth, hesitation, challenges and the changing face of BI in the cloud are at the heart of a new report authored by Saugatuck Analyst Bruce Guptill, entitled, “Saugatuck’s Boundary-free Enterprise Model: Concept, Impact and Guidance.” Saugatuck defines the “boundary-free enterprise” as an amalgamation of analytics, cloud, mobile and social technology, a collection of emerging trends that goes by other names across research firms.

On its own, business intelligence implementations have been challenged by issues such as data accuracy, adoption and cost, though BI has settled into more of a mature role with enterprise data over the last few years. Saugatuck cites that many BI functions can be accomplished in spreadsheets, as those maligned-yet-entry-level solutions have grown better at functions such as direct integration of Web queries or graphing, dismissing the overt need for a new BI solution in the cloud. Another problem is the introduction of potential issues around data location with BI operations and software moved to the cloud, as well as accompanying issues for better security between on-premise and deployed data and applications, according to the report. Similarly, Saugatuck points to integration of BI with cloud sources and on-premise operations as the “dominant issue” in this market over the next three years.

Even with those barriers, Guptill says there are strong cases for the reach and scalability of BI in the cloud, which has reduced core problems of access and delivery of enterprise data. Under it all rests the desire and ingestion of more data, where cloud shows the most promise to drastically alter the look of BI, says Guptill.

“I’ve never met any business or IT leader who complains about not having enough data. The complaints have always centered on how to find, access and effectively utilize the data available. With cloud, we have the reach and scale of data access that removes most barriers to finding and accessing data, hence the rapidly-accelerating interest in big data analytics,” Guptill says. “But where big data and traditional BI alike are most likely to fail is in data coordination and management – i.e., MDM – and then integration of that data into processes. We have practically unlimited data available, now we really need ways to manage it, quality-control it, secure it, cleanse it, etc. That’s the next big thing for cloud BI and big data alike.”

As it relates to the cloud, Guptill and Saugatuck outline a few immediate possibilities for mounting uses of deployed BI, such as:

  • Instant propagation of updates and changes, especially with changes in data sources and new types of analysis.
  • Secure sharing of specific and up-to-date information with partners and the supply chain.
  • Access to other cloud data, such as SaaS transactional data or unstructured content from social networks.
  • Capability to cost-effectively support a wider variety of initiatives, including one-time analyses, trial deployments and agile development.
  • Integration between external and internal clouds, and between external and internal data stores and multiple clouds.

On the vendor side the ever-increasing array of analytic capabilities packaged into BI offerings in an on-demand format – think IBM Cognos or Pentaho’s platform – works to “obscure” differences and costs across all offerings for the enterprise data customer, according to Saugatuck. Certainly, a wider range of BI capabilities is to be expected as the cloud grows in prominence, though the reports states that the ability to parse desirable elements is leading to three needs: data scientists and new analytic experts who understand underlying data for building and testing BI tools; template solutions for specific industry demands; and managed, consultative BI vendors creating PaaS-based solutions.
Saugatuck members can access the report here. Non-members can download the report for a fee here.

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