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 INPUT: Acxiom Corporation collects 300 million individual demographic records.  OUTPUT: Who is going to default on a loan.  Q: How do you process.

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Presentation on theme: " INPUT: Acxiom Corporation collects 300 million individual demographic records.  OUTPUT: Who is going to default on a loan.  Q: How do you process."— Presentation transcript:

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2  INPUT: Acxiom Corporation collects 300 million individual demographic records.  OUTPUT: Who is going to default on a loan.  Q: How do you process this input to output?

3  INPUT: Disney crowd estimates for 4 parks and 365 days of data.  OUTPUT: Best time to visit, best sequence of parks to visit.  Q: How do you process this input to output?

4  BI Systems use information technology (hardware, software, but even algorithms) to find patterns, relationships, and trends.  Data  (MIS)  Information  Information  (DSS)  Good Decisions  Information  (BI systems)  Knowledge

5  Reporting Tools ◦ Examples: Pivot Charts & Online Analytical Processing  Data Mining Algorithms ◦ Examples: Apriori Algorithm for finding association rules  Knowledge Management Tools ◦ Examples: IBM’s email knowledge bank

6  TPS – Transaction Processing Systems  PCS – Process Control Systems  MIS – Management Information Systems  DSS – Decision Support Systems  EIS – Executive Information Systems  ECS – Enterprise Collaboration Systems

7 People/Machines  (TPS)  Data People/Machines  (PCS)  Data & Routine Decisions Data  (MIS)  Info. & Routine Decisions Information  (DSS)  Complex Decisions Information  (BI)  Knowledge Information  (EIS)  Strategic Decisions Data & Info  (ECS)  Data & Info.

8  Old problem: Too much data ◦ figured out some solutions  New problem: Too much information ◦ Moving from info. to knowledge is a bigger problem ◦ Where humans are still needed

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10  Pivot Chart Lab & Logic ◦ We will learn how to make accurate predictions (knowledge) given raw data about behavior ◦ Excel will be our tool  Market Basket Lab ◦ We will find the strongest product associations (knowledge) given millions of possibilities (raw data) ◦ Access with be our tool  Large companies pay $millions for sophisticate tools to do these things

11  Intro Lab ◦ Getting to know the procedures  CMCC Lab ◦ Word is just a document maker ◦ Google Docs is more of an Information System  GIS Lab ◦ First DSS example ◦ Data  Information ◦ Tables  Maps  Reports  Excel Lab ◦ More than just an accounting calculator ◦ A tool for automation and information processing ◦ Searching (vlookup) and logic (if statements)

12  Reading is listed on the schedule  Review the lab


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