Searching for Effective Enterprise Information Management
The goal of EIM is to help locate and transform an organization’s data into meaningful information while managing its distribution so everyone can perform their jobs more efficiently and effectively. The key to success: search capabilities.
- By Mike Schiff
- December 2, 2009
Although there are numerous definitions of enterprise information management (EIM), I agree with TDWI, which defines it as “a best practice for creating, managing, sharing, and leveraging information in an enterprise, holistic manner that’s aligned with strategic, data-driven business objectives” (see Note). I further believe that the goal of EIM is to help locate and transform an organization’s structured and unstructured data into meaningful information while managing its distribution so that employees, customers, and partners can perform their jobs more efficiently and effectively.
In addition to ensuring consistent, high-quality data as the basis for any analyses and reports, to be useful, an EIM initiative requires that business users be able to locate the information that they need, when they require it.
Many major business decisions are based on collaboration among the decision makers and their advisors; this requires the ability to quickly locate and share information. The most insightful reports and analyses are of little value if they are not available when they are needed. For example, if Fred in accounting is a self-sufficient BI power user and has generated a report that can benefit others in his organization, Fred’s report is of little value if it is viewed by the decision makers after a decision is made; it must be available to them during the decision-making process.
The goal of making business intelligence more pervasive within the enterprise has resulted in BI vendors making their products easier to use by non-technical business users. In some cases, they’ve modified the user interface; in others, BI vendors developed new, simplified products that, although lacking some of the features or capabilities of their top-end offerings, were still suitable for many end-user self-service analysis needs.
This attention to ease of use has empowered additional users to use BI technology without constant IT involvement and handholding and has helped make BI more pervasive. However, it has also resulted in the proliferation of reports and analyses; it raises the new challenge of determining if a desired report or report template already exists or if a new one must be generated.
Many BI vendors recognize this and have enhanced their product portfolios and BI platforms with features that allow organizations to catalogue reports and analyses while providing users with powerful, yet simple-to-use, search capabilities to find them. Furthermore, several BI and data integration vendors also help users search for source data for their reports and analyses as well. The combination of “Google-like” enterprise search functionality with business intelligence technology is no longer a dream.
I believe that cataloguing and search capabilities are important components of any enterprise information management initiative. As they continue to expand and improve, they will facilitate true BI pervasiveness and serve to further empower the user community.
However, unless users are able to find existing reports and analyses, it will also result in much duplication of effort and analyses inconsistencies. If your organization’s EIM initiative doesn’t encompass report cataloging and search capabilities, you must seriously consider the need to provide them. Most enterprises are searching for ways to improve their information management capabilities and robust search functionality may just be part of the solution they are seeking.
Note: Philip Russom, senior manager of TDWI Research. Enterprise Information Management: In Support of Operational, Analytic, and Governance Initiatives. TDWI Monograph Series, March 2009.
Michael A. Schiff is founder and principal analyst of MAS Strategies, which specializes in formulating effective data warehousing strategies. With more than four decades of industry experience as a developer, user, consultant, vendor, and industry analyst, Mike is an expert in developing, marketing, and implementing solutions that transform operational data into useful decision-enabling information.
His prior experience as an IT director and systems and programming manager provide him with a thorough understanding of the technical, business, and political issues that must be addressed for any successful implementation. With Bachelor and Master of Science degrees from MIT's Sloan School of Management and as a certified financial planner, Mike can address both the technical and financial aspects of data warehousing and business intelligence.