Business Intelligence and Knowledge Management

This week we expand upon previous topics. We've already discussed complex business systems that can gather a lot of data, and we've also discussed databases and data warehouses. Once you have all that data being collected or already stored, the next step is to take advantage of it by analyzing it for potential opportunities. That's what this week's discussion is about. The outline presented here is intended to help point out important topics and terms, but is not intended to replace the lecture (or the text).

Objectives

• explain what data mining is
• explain what online analytical processing is
• describe how business intelligence can provide benefits to an organization
• describe how knowledge management can provide benefits to an organization
• explain why it is important to know about BI and KM applications

Business Intelligence

• BI: (Business Intelligence) software tools designed to find patterns and extract useful information out of databases (primarily data warehouses)
• The two primary uses for data warehouses are data mining and online analytical processing.
• data mining: the process of selecting, exploring, and modeling large amounts of data to discover previously unknown relationships that can support decision making
• data mining has four objectives
  • sequence or path analysis: finding out what events lead to other events
  • classification: finding out what categories facts belong to
  • clustering: finding previously unknown groups of related facts
  • forecasting: finding patterns in data that can lead to future predictions
• a sampling of data mining applications (listed in the text):
  • predicting customer behavior
  • identifying common characteristics of customers who buy particular products
  • finding out why customers switch to competitors
  • identify patterns associated with fraud
  • selecting potential customers for direct marketing campaigns
  • choosing what items to display to an online shopper based on their previous history and the history of similar customers
  • discovering what items sell well together
  • discovering trends
• OLAP: (OnLine Analytical Processing) provides an interface to the user where large amounts of data can be filtered, categorized, summarized and displayed quickly
• drilling down: a process by which one starts with tables containing broad information and gradually retrieves tables containing more and more detailed information
• check out www.fedscope.opm.gov/ for a great example of an OLAP application which allows you to try out "drilling down"
• dimensional database: database organized so tables show summaries and ratios of raw data; this speeds up processing time for OLAP applications
• multidimensional database: see dimensional database
• The text contains many examples of how various companies have used OLAP to detect problems and opportunities. Read them.
• Other systems, such as CRM (Customer Relationship Management), often have data mining and OLAP applications integrated into them
• dashboard: a name given to the user interface of BI tools when they present a handful of results in a easily interpreted graphical format; gauges that look like speedometers may have vertical indicators when everything is fine, but be off vertical for non-optimal conditions; maps may have sections that show up in red when data indicates a problem in an area; this way the user isn't always trying to analyze the numbers

Knowledge Management

• KM: (Knowledge Management)
• KM is the combination of activities involved in gathering, organizing, sharing, analyzing, and dissemination knowledge to improve an organization's performance. [This is directly from the text]
• Organizations often have someone who has knowledge in an area, but they don't know about it. Therefore, time and effort and expense are often wasted while another employee seeks that knowledge elsewhere.
• Employee knowledge networks can be used to disseminate information about who has expertise in a particular field. Often, the most important thing to know is where to find the information that you need.
• The Web is one of best ways of disseminating (and collecting) knowledge. The biggest problems with the Web are that the information may be totally unreliable and the coverage of different areas of expertise is often inconsistent.
• autocategorization: great for classifying data being stored so it can be later retrieved; in many ways, this is what Google already does with the Web
• automatic taxonomy: synonym for autocategorization
• knowledge worker: someone who works at developing or using knowledge