Accounting for Interdepartmental Language Barriers – Accounting and IT Part 2

Last week we were talking about the language barrier between Accounting and IT.  I managed to maneuver the conversation to the more specific area of IT known as Business Intelligence (BI) in a laughably transparent attempt to further my own agenda.

Providing some standard B.I. terms without definitions, I was looking to gauge your understanding of typical BI-speak through a quick game of word association.  There were no responses.  I figure I’ll probably need to establish myself more before I can expect comments.  I’m also going to assume there is a vague understanding of these terms.  Taking a line from The Simpsons when Bart’s teacher asks him if he knows Long Division, Bart replies, “I know of it”.  I would argue these are the “I know of it” terms of BI for an average accountant.

Let’s define them:

  • Business Intelligence (BI): supporting better business decision-making by transforming data (or transactions) into meaningful information about historical, current, and future operations.
  • Performance Management (PM): setting goals/metrics and measuring the results.
  • On-Line Analytical Processing (OLAP): a structure for data that allows fast analysis typically displayed in a matrix (pivot) format.  Data needs to be in a block where columns define the fields and each row is a complete record.
  • Analytical Applications: software that facilitates B.I.
  • “Slice & Dice” and Drill down: this might not need explanation. The former is to chop up the data into different views, and the latter is a buzzword that simply refuses. to. die.(<– awesome list from BBC).
  • Data Mining: is using computers to find patterns in data.
  • Data Visualization: a graphic representation of data; an area that is producing some great innovation right now!  It proves that Data Visualization is no longer just for the super-geeky.
  • Business Intelligence Dashboards, Scorecards: the former are a collection of visual gauges for tracking business performance, the latter has evolved from the specific program of business evaluation made popular by the book called “The Balanced Scorecard” into meaning any kind of general business Report Card (parent’s signature required).
  • Key Performance Indicators (KPIs): are quantifiable measures representing the critical success factors relevant to the business.  To really work, this should be limited to a handful of metrics, the most meaningful ones.
  • Data Shadow Systems or Spreadmarts: Again, these are separate terms. Shadow Systems (or Shadow IT) is any IT configuration created outside the supervision of the IT department; it includes Spreadsheets and their authors!  Spreadmart refers to the expanding number of spreadsheets inside your business.
  • Data Warehouses (DW): you are combining data from multiple sources into one big pile.
  • Data Marts (DM): a subset from the Data Warehouse, think of it as a truckload being hauled away from the loading dock of your Data Warehouse going to your monthly reports.
  • Data Integration: is a concept describing the retrieval and organization of business data from various sources producing a unified view for the end user, easier said than done.
  • SOA (Service Oriented Architecture): in broad terms this is a software structure that separates the core development code (stuff that doesn’t change frequently) from the more volatile aesthetic code for, say, website design (that does change frequently).
  • SaaS (Software-as-a-Service) or On-Demand Software: this is software accessed through the internet.  In other words, there is no installation of software to your computer or your company’s servers.
  • Cloud Computing: Larry Ellison’s (Oracle CEO) famous rant notwithstanding, this is accessing computing power from, what amounts to, a computing utility provider outside of your own servers. Just like you buy electricity from the power company, you can now buy computing power from these “Cloud” companies.
  • Dimensions & Facts: succinctly summarized here by Ralph Kimball at Dimensions are “the smallest tables in the data warehouse, and the real “meat” is actually the set of numeric measurements in the Fact tables” going on to say, they are “the entry points, the labels, the groupings, the drill-down paths” for your user interface.
  • Relational Database versus Columnar Databases: First, a Relational Database can just be visualized as an organized excel table with columns at the top all labeled and the values down the rows in those ‘named’ columns.  Think of a Columnar Database in the same way, but parsing each cell to quickly respond to any user question.
  • Unstructured Data: business information buried in emails, memos, notes, etc.
  • Metadata Management: perhaps a confusing term initially, it involves storing information about other information.  For example, a report export has hidden information that creates the structure for the report, like lines on a page.

So, I hope you know a little more now than you did before reading this.  Remember to check out the links throughout the article for more information, and also remember to subscribe to this feed for more Business Intelligence for non-techies content.

Last link: Enterprise Performance Management site.  This site looked pretty cool, but it didn’t quite “fit” in the definitions list.



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