Maximising your information resources means being able to access all of your data, regardless of where it resides and irrespective of the format it may be in. It doesn’t matter whether we are talking about analytic applications, business intelligence or reporting: without data these have no meaning or value and with only some of the data they will lack important information and do not provide the optimised resource that they should.
Large organisations will typically have multiple databases spread geographically. They will probably make extensive use of spreadsheets. They will have content management stores. They may well have NoSQL databases implemented alongside their data warehouses. It is quite likely that they will have some data in cloud-based or SaaS (software as a service) environments. A lot of the relevant data that you might want to explore will be in ERP, CRM or similar applications. In other words, relevant information about, say, customers may be in dozens, hundreds or thousands of locations. We know companies where this is measured in tens of thousands.
The question becomes: how do you combine all relevant data about any particular subject in a way that makes it easy for business people to find the information they need? First of all, of course, you need to know where all your relevant data is located. This is not a trivial task in large organisations. However, a discussion of the issues involved is outside the scope of this paper: a separate white paper “Understanding Information Landscapes” will be published by Bloor Research in the near future, which will discuss this and related issues such as data governance. Here, we are going to assume that you know where your data is and that it is reliable but that doesn’t answer the question of how you are going to pull all the data together.