IBM Industry Data Models in the Enterprise
Enterprise data warehouse (EDW) and business intelligence (BI) practices have been developing rapidly over the past couple of decades. Database design, data modeling and analysis go back even further. Along the way, vendors have developed different ways to give organizations an alternative to “starting from scratch.” Packaged BI and reporting templates are examples of pre-built, pre-designed tools that a company can adopt to move their analytic train down the line quicker and easier.
Also, many industries have become highly specified, even commoditized. Either due to government regulations or the nature of the business, industries like banking, healthcare, insurance and retail have developed models, processes and services that are very similar. When you visit a bank, you will probably know what to expect, because it is highly likely this bank operates in a similar fashion to the last bank you visited. Certainly, banks differentiate themselves competitively by improving customer interaction (integration and automation of the customer experience without losing a human touch), community involvement, product innovations and removing consumer barriers, but at the end of the day, you make a deposit, you cash a check, you open an account, you take out a loan, et cetera.
Over the past two decades, IBM has worked with hundreds of companies across a number of industries on data warehouse engagements. Based on the experiences of these engagements, IBM synthesized its knowledge and expertise of the information needs specific to several industries. The result was the development of a set of Industry Data Models that leverage their expertise and best practices.
An IBM Industry Data Model is a pre-built model specifically designed for an industry’s data needs. IBM Industry Data Models can jumpstart an organization down the path towards a comprehensive analytics environment by applying proven best practices in data modeling to self-contained units of business functionality.
The objective of this whitepaper is to give information technology leaders an understanding of IBM Industry Data Models, their components, their usage and how they fit in the overall information ecosystem of an organization. Important considerations, such as benefits, trade-offs, customization of the models, are examined. With the information presented in this paper, technology decision-makers will gain the knowledge needed to make an actionable decision on whether an IBM Industry model is a good fit for a situation and how best to lead a successful implementation. Finally, the paper concludes with an overview of models specific to each industry and a case study interview with an Enterprise Data Architect of a major financial institution that uses an IBM Industry Data Model.