As Gartner Research pointed out, by 2020, IT will generate $225 Billion in revenue for Social, Mobile, Analytics, and Cloud (SMAC) market. The foundation of the success behind these areas are information management and delivery. What is Enterprise Information Management (EIM)? EIM is the art, science, and management of building actionable intelligence with available data. EIM principles focus on forecasting the future with data from the past and exploring new avenues and opportunities with unexplored data. From strategy and advisory positions, to consulting and business intelligence positions, EIM has many roles and skillsets utilized by organizations.
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EIM can be categorized into Knowledge (Predictive Analytics), Information (Operational reporting, social media, benchmarking, data warehousing), Information Management (Data Quality, Master Data Management, Data Governance) and Data Management (Big Data, Database Architecture, Unstructured Data). Each of these areas have an associated people, process, technology, and data skillsets aligned to them.
Although EIM is a mature process with well-defined goals, the biggest challenge for an organization is the company wide culture to adopt EIM principles. The data governance arm of EIM acts as a legislative body introducing data policies, standards, and accountabilities, which might include business and IT transformations. This will create competition, insecurity, and extra work in addition to their day to day jobs initially. However, the return of investment can be seen very early if EIM principles are executed correctly. In fact, companies hiring Chief Data Officer (CDO) and Chief Analytics Officer (CAO) have become industry standards even in smaller organizations providing accountability and credibility.
In my future blogs, I will talk about some of the EIM arms and define what their roles and responsibilities are.