1 / 12

Comprehensive BI System Review and Learning Path

Explore the fundamentals of Business Intelligence (BI) systems, from understanding data processing to making informed decisions. Learn about BI tools, algorithms, and techniques to convert data into knowledge.

bary
Télécharger la présentation

Comprehensive BI System Review and Learning Path

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Business Intelligence &Exam 1 Review

  2. Business Intelligence (BI) • 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. Business Intelligence (BI) • 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. Business Intelligence (BI) System • 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. BI Systems includes • Reporting Tools • Examples: Pivot Charts & Online Analytical Processing • Data Mining Algorithms • Examples:AprioriAlgorithm for finding association rules • Knowledge Management Tools • Examples: IBM’s email knowledge bank

  6. Recall • 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. Background 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. The Big Problem • 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

  9. What we will learning soon • 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

  10. What we have done (review part) • 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)

  11. Things to study • Reading is listed on the schedule • Review the lab

More Related