The information management (IM) technology market is undergoing a revolution similar to the one in the business intelligence (BI) market. We define information management as the acquisition, organization, control and use of information to create and enhance business value. It is a necessary ingredient of successful BI implementations, and while some vendors such as IBM, Information Builders, Pentaho and SAP are in addition integrating their BI and IM offerings, each discipline involves different aspects of the use of information and will require it sometimes integrated and sometimes separate.
Some might consider information management as the “plumbing” behind BI. They take it for granted and only notice when it is missing. We have a more holistic view. Our recent benchmark research on business analytics shows that, for example, organizations struggle to collect all the data they need, with two-thirds of them stating they spend more time in data related activities than analytic ones.
Three key issues are driving our information research agenda in 2011:
1) Combining all the sources and types of data into an integrated information architecture.
2) Enabling organizations to manage and analyze larger volumes of information.
3) Providing accessibility to information throughout the organization.
We’ll be updating our information management benchmark research this year to see how these central issues are impacting IM overall. In addition we will focus on five technology innovations my colleague has identified as the business technology revolution in 2011: cloud computing, mobile technologies, social media, analytics of more types over more data and collaboration. Let me flesh out each of these a bit as they impact the evolution of IM.
As I pointed out in “Clouds Are Raining Corporate Data,” cloud computing is having an increasingly large influence over the IT landscape. It’s likely that, whether you realize it or not, corporate data exists and/or is migrating outside the walls of your organization. Cloud-based applications and services raise information management challenges that don’t necessarily exist in on-premises deployments. We’re investigating these issues now in our Business Data in the Cloud benchmark research program and where many new providers dealing with cloud data like Dell Boomi, Jitterbit and Snapdata play into the existing landscape of IBM, Informatica, iWay Software, Oracle, Pervasive and Syncsort to name just a few.
Mobile technologies are enabling organizations to deliver information to users when and where they need it. They are one of the forces driving cloud adoption as organizations look to make it easier to deliver applications to users regardless of their location. Mobile applications also are consuming and producing more location-related information and creating a need to manage this kind of data.
In the world of information management, social media has created entirely new challenges. Most social media data is unstructured text and is forcing organizations to embrace text analytics to deal with it, in many cases for the first time. The volumes of social media data and the speed with which it should be collected and analyzed also present new challenges. From an IM perspective, organizations must learn how to solve these challenges while enforcing appropriate data quality, data governance and life-cycle management policies.
Analytics present an additional set of IM challenges. The necessity of managing more data and different types of data has led to the adoption of large-scale technologies such as Hadoop. In research that is under way now we are researching the various ways of dealing with these huge data volumes and the role of Hadoop in that process. Predictive analytics also create IM challenges. Sampling, which is a key to producing unbiased predictive models, may or may not become less critical as database analytics grow in popularity. The models and the scores that such analytics produce are another form of data that must be managed and retained, often for compliance and auditing purposes. We’ll be studying these issues as part of predictive analytics benchmark research that will commence in the first part of 2011.
Collaboration provides a means to communicate and extend the processes of IM. It creates a new channel not only for delivery of information but also for input into the delivery process. Using collaboration tools such as Twitter, Chatter or Tibbr can help organizations use data and related information by involving more people. This wider audience collectively contains more knowledge about the underlying data and can also comment on its quality, which ultimately will lead to better data and more trust in it. Collaboration tools also provide a mechanism to link the workflows of information management with the constituents involved in the process.
Information management continues to evolve and grow, somewhat to my surprise as indicated in my recent assessment of Informatica. These changes present challenges for IT groups and lines of business alike. With our IM research agenda, we hope to provide useful information to both functions and help you navigate together through this changing landscape and achieve the goal of creating and enhancing business value.