Rob Armstrong wrote an interesting post, What do you mean by BI?, on the Smart Data Collective in which he outlines five different levels of business intelligence along with the IT and user requirements for each. First he notes that he “like(s) to read an acronym backwards. BI is not about business intelligence, it is about having enough intelligence regarding your business that you can make, and take, relevant, timely, and profitable actions.” We would agree. Here are the five levels with the IT and user requirements for each in Rob’s words.
Level 1: “Basic Canned” Reports: - users have no ability to change the content of the report and receives latest version of pre-determined output. “Highly optimized by IT; Well defined by Users.”
Level 2: “Canned Ad-Hoc” – users target parameterized dimensions for pre-determined and pre-optimized reports. “Highly optimized by IT; users determine “typical” dimension blocks.”
Level 3: “Customized Canned Ad-Hoc” – users can define dimension boundaries and also determine columns or calculations that appear on the report. “Optimized by IT; KPI’s defined by users.”
Level 4: “Create your own” - user have free reign to determine the columns, dimension ranges, and even create new metric calculations limited only by their security access needs. “Users understand SQL processing and creation. May also create temporary tables or store results.”
Level 5: Data Mining – in prior levels users are asking questions to get answers. In data mining the “user is asking questions to understand what questions really need to be asked.” “Users trained in data model and SQL practices.”
Let me add a sixth level:
Awareness Engine™ - users can set and explore topics and subtopics within a targeted set of content sources and discover new content beyond predetermined expectations in real time. There is no requirement for IT to be involved at all as it is a SaaS application. There are no technical requirements for tool use such as data modeling or SQL practices. The more the user knows about the content topics, the better they are able to optimize value from the tool by seeing the important anomalies.
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