Deciphering The Maze Of Business Intelligence Analytics Technologies

Image from http://loobenji.deviantart.com/art/Maze-130232999Since 2010, when Forrester asks about organizations’ top software priorities, the number one ranked priority has been business intelligence (BI). Continued economic uncertainty and major industry-changing dynamics like mobility and the shift to digital business put a premium on data and information. The ability to effectively extract, analyze, and interpret vast quantities of data has simply become critical to business strategy decisions. Investments in BI analytics reflect the importance being placed on these technologies.
 
However, the large number of analytics technologies at differing levels of maturity and adoption has, in many cases, left planners of BI confused as to which technology should be adopted and for which scenario.
 
As a result, my colleague, Holger Kisker, and I used Forrester’s TechRadar methodology to examine 15 key analytics technologies to identify their usage scenario, current maturity within the enterprise, future trajectory, key vendors, as well as estimated costs for implementation. The technologies analyzed included the following: reporting, dashboards, performance analytics, embedded analytics, web analytics, process analytics, predictive analytics, OLAP, advanced visualization, metadata-generated analytics, location analytics, search/discovery, streaming analytics, nonmodeled data exploration and discovery, and finally text analytics. Forrester clients can read the full report here.
 
In analyzing the analytics technologies, we found that:
 
  • Investments in more widely adopted analytics technologies will shift to scope extensions. Reporting has already been implemented by 81% of firms and 58% have implemented dashboards (according to Forrester’s Forrsights Strategy Spotlight: Business Intelligence And Big Data Survey, Q4 2012). It is perhaps surprising that penetration for these technologies is not closer to 100%, and this reflects the continuing journey which BI needs to make. However, as organizations continue to invest in these technologies, they will increasingly focus on scope extensions because newer, more innovative analytics technologies — such as predictive or location analytics — can be embedded within these traditional technologies to create whole new use cases.
  • Many nascent technologies will see rapid adoption and move out of their current niche usage. The hype surrounding many analytics technologies — such as predictive analytics — masks the reality that their adoption and usage currently remain limited to some relatively specific instances. For example, according to the same survey, just 21% of companies have implemented predictive analytics. The potential of these technologies, however, has already stimulated wide interest among planners of BI as well as dollar investments. As a result, the maturity and adoption of some of these technologies will rapidly and significantly increase in a relatively short period of time.

BI analytics will be a key priority for organizations in the future. The confluence and combination of these technologies will spur the development of new possibilities as organizations come to rely on information and the analysis of vast swathes of data for their competitive survival.

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