I predict that 2012 will bring in an explosion of interest in Social Analytics, Social Business Intelligence, and the use of post-relational database technologies like Hadoop/HBase. In 2011 the world observed the power of social media outlets like Twitter, Facebook, blogs, and others on Middle Eastern human rights movements; corporate greed and customer service snafus; and the most recent Occupy Wall Street movement. In 2012 organizations will be exploring how they can glean valuable and actionable information from all of this unstructured, publicly available, and passionate information.

[Editor's Note: This post is part of the annual "Cutter Predicts ..." series, compiled at the Cutter Consortium website.]

I see the growing adoption of tablets — by both consumers and companies — as really jump starting the corporate use of mobile BI. I base this on responses I’ve received from my Data Insight & Social BI Advisor readers, as well as from survey respondents, who have informed me that their mobile BI initiatives call for tablet devices to play a significant role, particularly for sales and field support. Tablets feature much larger screens that lend themselves very well to supporting mobile BI apps. Basically, enhanced screen size places considerably fewer constraints on the amount of information end users can download and interact with (as compared to even the most advanced smartphones). Tablets also tend to offer additional on-board processing power that can be used to enhance data visualization, charting, and other interaction capabilities. Additionally, organizations want to Read more …

All the focus on big data is missing the point. Yes, high performance computing architectures let us analyze very large data sets. And yes, that is interesting and helpful. But let’s go with a thought experiment here. Imagine the following:

Real-time data feeds from all source systems; Incremental, multi-generational real-time data feeds and data storage so all prior versions of data are accessible; The end of batch processing, nightly loads, ETL or other boring stuff in order to prepare data; All queries you can dream of (well, maybe 98% of the queries) running in in less than a second; All the rest of the queries running in minutes, not hours and yes, even crazy Cartesian products, intended or not; The ability to construct a hierarchy of models that users can then interrogate themselves, with queries on those models running in Read more …

This month, Cutter unveiled its redefined BI practice, Data Integration, BI & Collaboration. I know it’s a mouthful, so let’s just call it “DBC” for short. As the new Practice Director, my aim is to shape this practice to best address your needs, but more importantly to continuously adapt as your needs change. I also suspect you are looking for Cutter to assist you in staying aware of emerging ideas and trends that might benefit your organization. Please consider this post an open invitation to join an ongoing dialogue that will help me shape this practice appropriately. I hope you’ll share your questions, ideas, and feedback to make this venture a success.

The practice name conveys the fact that traditional BI, the organization and reporting of corporate operational data, is no longer the competitive Read more …

“Social media” is one of these phrases that has emerged in recent years for which there is still not a single, broadly accepted definition. Thus, every author tends to propose his or her own. This is not just vanity; it is also the sign of an immature and rapidly evolving field.

In a recent Executive Update, Cutter Fellow Steve Andriole and Cutter Senior Consultant Vince Schiavone define social media by extension, listing the following components (with my examples added in parentheses):[1]

Social networks (LinkedIn) Blogs and microblogs (WordPress and Twitter) Forums and message boards (Yammer and Google Groups) Multimedia sites (YouTube and Flickr)

A definition made up of a list has some drawbacks: it does not tell you what social media is not, and it does not leave room for the next new thing. An interesting “intentional” definition was given by Vince Read more …

Congratulations to Cutter Consortium Senior Consultant Ken Collier! His latest book, Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing, was named one of the “11 Books to Recharge Your Leadership Skills” by CIO-Insight.

A leading expert with Cutter’s Business Intelligence and Agile Product & Project Management practices, Ken is the developer of the Agile Business Intelligence (Agile BI) methodology, which combines agile methods with data warehousing, business intelligence, and advanced analytics. He has successfully adapted agile techniques to DW/BI to create the Agile Analytics style. He continues to refine these ideas as a technical lead and project manager on several agile DW/BI project teams.

As CIO-Insight points out, Ken’s latest book is “a how-to on bringing new agility to data warehousing features, resulting in valuable business intelligence and dramatically reduced project risk.” Find CIO-Insight’s complete list Read more …

Our research indicates that interest in predictive analytics and data mining has never been higher, and that organizations are increasingly turning to the technology to take their BI capabilities to the next level (i.e., the ability to predict who will be their best customers, which customers are likely to churn, and optimum performing suppliers, etc.). Moreover, organizations are not only using predictive analytics to analyze structured data, but are also applying text mining and analysis tools to analyze unstructured (text-based) information. (Please do let us know your opinion on the use of text mining and analysis by taking our survey at www.keysurvey.com/survey/347516/e8e2/ .)

A number of factors are driving the use of data mining and predictive analytics. More general trends  include that organizations have a great deal of data to analyze — so much data, in fact, that the Read more …

The question of whether an organization should build software or buy it dates to when the first significant COTS packages (typically for accounting, computer-aided design, or manufacturing resource planning) appeared on the market between 1970 and 1990. Search for “build vs. buy software” on Google, and you get 52 million results. Most of the results on the first pages are dated around 2001-2002, so one would think that the question has been settled, mostly along the following lines:

If you need a capability that is fairly generic, and will not in itself give you a competitive advantage (the way you apply it may be superior to how others do it, but the software itself will not make a difference), then you should buy a COTS package. This will not only give you the desired functionality earlier than if you developed it, Read more …

The Linked Open Data (LOD) cloud has doubled in size approximately every year since 2007 and is now collection of more than 200 datasets that offer more than 25 billion interlinked facts, available across widely diverse domains such as government, scientific, medical, social media, geographic, and other data. All of this publicly accessible data now comprises an estimated 395 million links between around 25 billion RDF statements. Starting in 2011, increasingly interesting and useful Semantically Aware Applications (SAAs), in the form of mashups against this semantically-defined data, will begin to proliferate massively. Look for governments (exemplified by www.data.gov in the United States and www.data.gov.uk in England) — in the continued spirit of transparency and accountability — to be leading the charge in this area.

[Editor's Note: This post is part of the annual "Cutter Predicts …” series, compiled at Read more …

It has been just over 50 years since preeminent IBM computer scientist Hans Peter Luhn coined the term “business intelligence.” And ever since then, BI has been viewed as getting information to the people who need it in a timely fashion and in a form that is easily consumed and acted upon (the right data to the right people at the right time). From those seemingly prehistoric days of data processing, when BI consisted primarily of monthly reports on green bar paper, to today’s splashy interactive graphics on wireless mobile devices, both the data that is available and the means with which to deliver it to the right people have changed dramatically.

But have these changes made a measurable impact in organizations, or have the results fallen short of the promises? Almost everyone has access to far more data in Read more …