The DW/BI Domain Functionally Broken Down
Value-Driven Data Warehousing
Information Management Online, May 24, 2007
"I am tired of IT people. They'll talk to you for half an hour about what they do, but by the time they're finished, you still don't have any idea what they've told you or why it's important," so complained a friend of mine in a recent conversation. What was the irritant giving rise to my friend's frustration? Ahem ... my own ineffective attempt to explain to him what it is that I, a data warehousing/business intelligence (DW/BI) practitioner, do.
Sometimes the right metaphor is helpful. It can clarify abstract concepts for the uninitiated and, even for the expert, be a means for synchronizing designs and vocabularies and analyzing problems. To that end, let me propose a metaphor for describing what DW/BI is all about and, perhaps more importantly, suggest where the field is broken: the metaphor is that of an information supply chain.
This metaphor - the information supply chain - is in some ways a simple extension upon thoughts already well developed by others, most notably Bill Inmon's Corporate Information Factory (CIF), and yet the supply chain metaphor doesn't seem to enjoy much use in the marketplace, at least not as a framework for holistically describing both the DW and BI, together.
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Inmon describes the enterprise data warehouse and the various satellite systems that surround it - operational data stores (ODSs); extract, transform and load (ETL); data marts, etc. - as similar to a brick-and-mortar factory. The factory inputs many disparate raw ingredients (data from all the company's operational systems), subjects those raw data inputs to a series of processes wherein the data is refined and integrated (ETL) and finally spits out a finished good on the other end (corporate information). Whether a practitioner leans more toward Kimball's dimension bus architecture or Inmon's CIF as the guiding vision for how to build a data warehouse (or like this author you feel the two approaches are more complementary than contradictory), Inmon's metaphor is simple to understand and helpful for explaining what data warehousing is all about.1
Extending the metaphor to encompass the field of business intelligence is beneficial, since definitions of BI seem pretty slippery, and it can be unclear how BI overlaps or is different from the enterprise data warehouse. I believe the reason for this confusion, at least in part, comes down to how the term "BI" is often used - that is to say - it is used to convey purpose, rather than function. BI is typically defined as: the collection of tools and techniques used to help companies make better decisions. This definition is very broad. It expresses a worthy purpose, but it casts a huge net within which almost anything can fall and thereby blurs important distinctions.
Purposefully defined, the data warehouse falls under the BI umbrella, as do reporting tools, as do data mining tools, as do spreadsheets, as could CRM, as could the complex corporate budgeting process or even the simple process of conducting status meetings between a manager and team, because all of these share the goal of "improving corporate decision-making." I've even seen a company that specializes in the imaging and management of paper records label themselves as providers of "BI services." Everyone wants to jump on the BI bandwagon because the term is trendy, analogically rich and expresses a worthy goal to which many aspire or can somehow lay claim. Overly expansive definitions, however, soon become worn out as they are too lofty and hyped to convey anything particular with force and clarity.
In that light, a functional definition of BI is more useful, and to aid in that definition, the supply chain metaphor is helpful. In short, if the data warehouse and its immediate satellite systems comprise an information factory, where raw data becomes corporate information content, BI represents the distribution channel for that content.
What does this mean? It means that the DW and BI components are separate yet linked pieces in the information supply chain. One integrates and manufactures content (the factory). The other disseminates that content to user-consumers (the distribution channel). One crunches large amounts of data on big, heavy-duty servers with long-running, complicated processing, not unlike an assembly line (the factory). The other ships that content out in smaller, more manageable bits to end users in attractive packaging (the distribution channel). One tends to place more emphasis on centralized processing and achieving economies of scale (the factory), while the other seeks to tailor content to the needs of a specific line of analysis or a targeted business process (the distribution channel). In short, the DW (the factory) makes content out of raw data, while BI (the distribution channel) picks up the content and reports it, charts and graphs it, helps users visualize it, "portalizes" it, rates and routes it, triggers alerts about it, triggers processes based upon it, and may even reoperationalize it - i.e., interpret it and suggest courses of action to an end user or even automatically execute those actions (for example, a BI system detects an unusual pattern in credit consumption on the part of a particular customer, suggestive of possible fraud or solvency issues, and automatically throws up an order block in the order management system for this particular customer while simultaneously triggering an alert for a service rep to begin investigating). This in a nutshell describes the interrelationship of the DW and BI components. Together they form an information supply chain, and the value of either one is diminished apart from the other.
So what?
Perhaps this metaphor proves helpful to those who are new to the field or aids those with more experience explain to an impatient business user or manager why it may not be possible to simply materialize and place on their desk within the next hour a report with some new piece of data (for like the physical supply chain, which a business user likely understands, the information supply chain involves negotiating a fair amount of complicated processes and machinery).
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