Below is a list of questions we commonly receive about business intelligence, data warehousing and our company. If you still have questions you would like to have answered, please do get in touch with us.
While many definitions exist, at Dataspace we define business intelligence as the art and science of delivering the right data to the right users in the right format at the right time. Business intelligence has evolved over the years from the simple act of writing and reading about commercial transactions, to manually created accounting financial statements that summarized many transactions, to computerized reporting tools and languages like COBOL, and finally to today’s interactive business intelligence and query tools.
For a number of reasons (see “Do I need a data warehouse?” below), it may be inadvisable to provide business intelligence directly off the operational systems that capture data. In these cases, organizations may create data warehouses. A data warehouse is simply a database that contains the information that, sometimes, underlies a business intelligence system.
Data warehouses and data marts are databases that isolate reporting and business intelligence from operational systems. This isolation may be necessary for a number of reasons including, A) complex BI queries might slow the operation of key functions or processes with connections to these systems; B) BI queries may be so complex that the run time will take longer than is optimal to meet user needs; C) Operational systems may regularly discard details that are not necessary for day-to-day operations but vital to trend analysis; and/or d) users may need to report against not just one, but multiple systems simultaneously. In cases like these, a data warehouse may be necessary. Remember, data warehouses are complex systems to build and maintain. They are sometimes necessary, but alternatives should be considered.
Even the most knowledgeable IT organization can fall victim to some mistakes that can cost them money and time. For example:
BI initiatives that are more about delivering data than about improving business processes or other actionable outcomes are much less likely to demonstrate a return on investment
While the terms data warehouse and data mart are thrown around loosely, at Dataspace we think of a data warehouse as a database that integrates data from numerous sources, acting as a clean source of truth for downstream data marts. A data mart, on the other hand, is a reporting database focused on the specific needs of a particular group of users (e.g. the finance data mart or the sales data mart or the distribution data mart).
While some technologies are better than others, there is no generic ‘best’. Instead, The best BI technology is one that meets user needs at a reasonable cost. Many organizations try to set corporate standards built around a ‘best’ technology; however, these organizations lose sight of the fact that there is no single BI user. Most organizations house a number of user communities, many with vastly different needs. Thus, it is possible – even likely – that rather than a ‘best’ BI technology, these organizations should be looking for the ‘best’ technology for a particular job or a particular group of users.
For over 15 years the data warehouse industry has been captivated by the seemingly opposite approaches of two industry luminaries, Bill Inmon and Ralph Kimball. Although careful study will show that the approaches are not as different as people think, Inmon is generally associated with building a data warehouse that integrates data from multiple sources and then feeds it to downstream BI tools and data marts. Kimball, on the other hand, is associated with building data marts and joining them together into an integrated whole.
Dataspace’s first rule is that pragmatism rules. Sometimes the Inmon approach makes the most sense, sometimes the Kimball approach does, sometimes you should do what we call “getting to Inmon on the back of Kimball”, and sometimes you don’t really even need a data warehouse. Give Ralph and Bill a rest, let logic and experience rule.
Dataspace is unique among BI consultancies for the following reasons:
Dataspace serves two primary audiences:
Our headquarters is located in the university town of Ann Arbor, Michigan. However, our client base spans the United States. In most cases, we travel to client locations when necessary and are very effective at performing work offsite when possible to keep travel expenses to a minimum.