BI Experts: Adoption Rates of Emerging Technologies and Methods in BI
A new TDWI survey shows that users will aggressively adopt emerging BI technologies over the next three years.
- By Philip Russom, Ph.D.
- October 23, 2012
Part of the fun of being in business intelligence (BI), data warehousing (DW), data integration (DI), and analytics is the constant stream of new and exciting hardware, software, team structures, and user methods. TDWI refers to these collectively as emerging technologies and methods in BI (ETMs).
Some ETMs are so new that they are truly just emerging -- for example, agile development methods for BI, BI in the clouds or as software-as-a-service (SaaS), event processing, Hadoop, MapReduce, mash-ups, mobile BI, NoSQL, social media, solid-state drives, and streaming data. Other ETMs have been around for a few years, but are just now being adopted by appreciable numbers of user organizations -- for example, appliances, competency centers, collaborative BI, columnar databases, data federation, open source, in-database analytics, in-memory databases, MDM, real-time operation, and unstructured data.
TDWI sees all ETMs being adopted steadily into the near future by user organizations, but which ones are being adopted the most aggressively? Those could be priorities for which savvy users should plan.
To answer that question, TDWI conducted a technology survey in late 2011. The survey presented a list of 30 ETMs, and asked respondents to identify those they have no plans for using, those they are already using, and those they'll adopt within three years. Survey responses reveal which ETMs are of little interest today (at least, to survey respondents) versus those that are already in use or will be soon. Here's a summary of what we found.
New BI techniques will see the hottest adoption over three years
Mobile BI tops the list; 29 percent of survey respondents said they're doing it today, whereas a whopping 57 percent said they're not doing it today but will within three years. After mobile BI come related BI techniques, such as real-time BI (28 percent today; 53 percent in three years), agile BI (32 percent; 47 percent), and advanced data visualization (36 percent; 43 percent).
Users plan aggressive moves into all things analytic
This includes predictive analytics; 38 percent of survey respondents said they're doing it today, whereas 46 percent said they're not doing it today but will be within three years. Other growing analytic ETMs include in-memory analytics (30 percent; 43 percent), text analytics (14 percent; 39 percent), and big data analytics (22 percent; 38 percent).
The most dramatic growth rates for ETMs involve a jump of 20 percent or more
If you compare the percentage of survey respondents using an ETM today to the percent for the same ETM in three years, the delta identifies a few ETMs that are poised for very dramatic growth. These include clouds for BI/DW (9 percent today; 47 percent in three years), social media analytics (9 percent; 36 percent), and complex event processing (16 percent; 35 percent).
Some ETMs are already well established
A number of ETMs already have a large foot in the door, including Web services/SOA (54 percent of survey respondents), self-service BI (47 percent), analytic DBMSs (42 percent), master data management (40 percent), data warehouse appliances (37 percent), and big data analytics (22 percent).
The newest ETMs need more time for adoption
Ironically, some of the most discussed ETMs today are those for which the most users have "no plans to use." For example, consider NoSQL DBMSs (82 percent of respondents have no plans to use them), Hadoop (72 percent), and MapReduce (68 percent). This is natural, given the newness of these technologies and the fact that it takes time for an ETM to move beyond its initial early adopters. In fact, these same ETMs are about to make that move, as seen by comparing the percentage of survey respondents using each today to that in three years.
For example, take another look at NoSQL DBMSs (3 percent today; 15 percent in three years), Hadoop (8 percent; 20 percent), and MapReduce (10 percent; 22 percent). Each is poised to jump 12 percentage points according to our survey results. Hence, if users' plans pan out, NoSQL, Hadoop, and MapReduce will go from rare to common in a mere three years.
The results of this survey are good news in that they show users embracing emerging technologies and methods (ETMs). It's important to do so, because ETMs can satisfy new business requirements relative to BI. For example, most of the ETMs mentioned here support some kind of analytics, and analytics have become critical to competing effectively, controlling costs, retaining customers, and understanding and leveraging business change.
Furthermore, through emerging technologies, a business can embrace new practices (social media analytics), delivery methods (mobile, self-serve), time frames (real-time BI), development paradigms (agile), and IT platforms (clouds).
If you'd like to learn more about emerging technologies and methods in BI, attend the TDWI Forum Emerging Technologies for Big Data Analytics on November 12-13, 2012 in Orlando, Florida. More information is available online at www.tdwi.org/OR2012.