Year in review: Top 9 Business Intelligence developments of 2011 (P2)

Part one of this three-part blog series – Year in review: Top 9 Business Intelligence developments of 2011 (P1) – discussed how the 2011 Business Intelligence (BI) market was akin to The Joker’s infamous line in Christopher Nolan’s The Dark Knight – “An unstoppable force meets an immoveable object” – while listing the first three major BI-related developments of 2011: Self-service BI, Collaborative BI and Mobile BI. Part two resumes the adventure at number four…

4. Social media analytics

As social media cemented its position as a vital and growing marketing tool for many corporations, the desire to apply analytics to the social media activities of customers also blossomed.

Forrester Research’s Senior Analyst, James Kobielus, wrote in January this year that: “Social media are the intelligence powering modern marketing” because social media has shifted much of the work involved in traditional market research – interviews, surveys, focus groups – and “intelligence-gathering to the customer.” We actively divulge information pertaining to brand sentiments and interactions, and naturally, organizations are all-too-keen to apply business analytics to our social media activities to harvest this potentially (highly) valuable information.

A recent UBM research report into social media analytics backed Kobielus’ assertions. The survey – How IT Decision Makers and Tech Marketers Are Using Social Media Today – surveyed ‘IT Decision-Makers’ and ‘Tech Marketers’ to uncover the usages for, and perceived importance of, social media platforms as information sources in the technology industry.

The survey found that IT Decision-Makers are spending 13 percent of their time on social networking sites to learn about industry trends and news, with 40 percent planning to increase their usage.

Unsurprisingly, Tech Marketers also placed heavy emphasis on social media platforms, with 43 percent agreeing that marketers must have a social media strategy in place, or be rendered uncompetitive.

5. Big Data

Big Data received an immense amount of attention during 2011. For the purpose of this discussion, Big Data has been defined as: “The overall volume of active data an organization stores as well as the size of the data sets it uses for its business intelligence and analysis”.

The continued and rapid expansion of corporate data assets has been well documented and discussed within the business analytics industry and the analyst community. However, much of the discussion revolved around hype. This was clearly evidenced by the inclusion of Big Data on Gartner’s 2011 Hype Cycle, which, according to Gartner, is already crescendoing towards the “peak of inflated expectations”. Now, does this mean that Big Data is somehow irrelevant? Not at all – just overhyped. Big Data doesn’t just mean attempting to collate and meaningfully interpret terabytes and terabytes and terabytes of data. Big Data is relative – if an SMB is struggling to work with gigabytes worth of data, then they (relative to their situation) have a Big Data challenge to resolve. Solutions and discussions need to be appropriately matched to reflect that truth. As industry expert Colin White said: “Stop debating size of big data and focus on use cases. It’s not just size. Data variety and workload types are more important.” For more on this topic, check out Yellowfin CEO Glen Rabie’s presentation at the Australian Software Innovation Forum’s The New World of Data conference: //

A recent benchmark report by Aberdeen Group (June 2011) – Future Integration Needs: Embracing Complex Data – revealed the biggest drivers / challenges for companies attempting to leverage value from Big Data (respondent organizations with data sets from 500 gigabytes to over 20 terabytes) as:

  • Increasing demand for management information (69%)
  • New analytic needs not well suited to existing data warehouse (67%)
  • Growing volumes of source data (41%)
  • Rapidly changing business needs require different management information (31%)

6. Agile BI

People talked about, but continued to fail in their attempts to define, Agile BI. Essentially, it can be encapsulated like this: Agile BI is the desire to swiftly respond to changing information needs and place fact-based solutions to critical business problems in the hands of appropriate decision-makers – a desire that was evidenced strongly by the continued ‘consumerization’ of BI. Now, Agile BI of course encompasses technologies, processes and cultures. Previously, we (Yellowfin) have attempted to define Agile BI in these three ways:

  • Technology: Actual easy-to-use and deploy technology and its capabilities and capacity to underpin agile development
  • Culture: A supportive environment for the introduction of a BI solution and its continued use
  • Process: The way in which BI is deployed and developed should be agile to meet the specific and changing needs of any given organization

A poll, conducted on TDWI’s official LinkedIn group last month, suggested something similar, with the majority of respondents stating that Agile BI encompassed:

Recent Aberdeen Group research, Agile BI: Three Steps to Analytics Heaven, defined Agile BI as a technical capability – empowering decision-makers with self-service access to business-critical information in shorter timeframes. The report distinguished a company’s ability to deliver Agile BI based on:

  • The availability of timely information to managerial decision-makers
  • The average time taken to add a column to an existing report
  • The average time needed to create a new dashboard

Survey respondents identified the top three strategic enablers for successfully delivering Agile BI as:

  • Empowering end-users with greater self-service (64%)
  • Creating a repeatable process-oriented approach to BI projects and their ongoing assessment (50%)
  • Empowering IT with the ability to react to BI demands with greater responsiveness (24%)

A recent Forrester Research report – Trends 2011 And Beyond: Agility Will Shape Business Intelligence For The Next Decade – authored by Principal Analyst, Boris Evelson, identifies four major technological areas / enablers of “next-generation” BI solutions that it believes are vital for achieving successful, agile, BI deployments:

  • Devoid of limitations: Encompassing adaptive data models, unlimited dimensionality, as well as data exploration and analysis
  • Automated: All BI processes and components wherever possible
  • Pervasive: Make BI available to all decision-makers wherever, and whenever it’s needed, via online self-service, mobile, social and integrated components
  • Unified: To eliminate knowledge silos

Speaking at the recent Gartner BI Summit in Sydney during 2011, Gartner analyst, James Richardson, said that Agile BI was more about people and processes than the underpinning technology. Richardson said the success of Agile BI projects depended, to a large extent, on the ability to close the gap between the business and IT portions of the organization, and that securing executive backing from across different business functions aided the process.

“Business people and developers must work together to make sure the gap between IT and the business is reduced,” he said.

Richardson also explained that business and IT needed to collaborate closely to construct an environment conducive to an Agile BI implementation, because the agile methodology states that reporting needs are constantly changing, and this state of constant change must be embraced.

“BI is the art of trying to hit a moving target,” he said. “About half of BI requirements change in the first year of a BI project.”

Where to next?

Tune in for part three of this three-part exploration of 2011’s defining BI developments. Then, hang about to see what this year’s influential BI elements will be in Yellowfin’s top ten BI predictions for 2012.

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