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The information architecture of the organization

The information architecture of the organization. MIS2502 Data Analytics. A Brief Review. This is what is commonly thought of as “database management”. This is the foundation for business intelligence. The Information Architecture of an Organization. Data entry. Transactional Database.

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The information architecture of the organization

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  1. The information architecture of the organization MIS2502 Data Analytics

  2. A Brief Review This is what is commonly thought of as “database management” This is the foundation for business intelligence

  3. The Information Architecture of an Organization Data entry Transactional Database Data extraction Analytical Data Store Data analysis Stores real-time transactional data Stores historical transactional and summary data Called OLTP: Online transaction processing Called OLAP: Online analytical processing

  4. The Transactional Database • Stores real-time, transactional data • Examples of transactions • Purchase a product • Enroll in a course • Hire an employee • Data is in real-time • Reflects current state • How things are “now”

  5. The Relational Paradigm • How transactional data is collected and stored • Primary Goal: Minimize redundancy • Reduce errors • Less space required • Most database management systems are based on the relational paradigm • Oracle, DB2, Access, SQL Server ? Which of these do you think is more important today

  6. What Else is There? • “NoSQL” (Not Only SQL): a catch-all phrase for other stuff • Better geared toward “Big Data” storage • More scalable • Faster storage and retrieval • Cheaper hardware requirements • Less oversight/management (in theory) • Out of necessity, rather than preference • Data is unstructured, must be parsed • Does not lend itself well to analysis Further reading: http://www.techrepublic.com/blog/10things/10-things-you-should-know-about-nosql-databases/1772

  7. Who is Using NoSQL?

  8. The Relational DatabaseAirline Reservation Example • A series of tables with logical associations between them • The associations (relationships) allow the data to be combined 1 n n 1 n 1 1 1 n

  9. Why more than one table? • Every reservation has a passenger and a flight • Passengers and flights have an ID number • Split the details off into separate tables 1 n n 1 n 1 • This is good because: • Information is entered and stored once • Minimizes redundancy 1 1 n

  10. Analyzing transactional data • Can be difficult to dofrom a relational database • Having multiple tables is good for storage and data integrity, but bad for analysis • All those tables must be “joined” together before analysis can be done • The solution is the Analytical Data Store Operational databases are optimized for storage efficiency, not retrieval Analytical databases are optimized for retrieval and analysis, not storage efficiency and data integrity

  11. The Analytical Data Store • Stores historical and summarized data • “Historical” means we keep everything • Data is extracted from the operational database and reformatted for the analytical database • Most analytical databases use a dimensional paradigm Extract Transform Load Operational Database Analytical Database Data conversion Query Query We’ll discuss this in much more detail later in the course!!

  12. The Dimensional Paradigm Data is stored like this around a business event… …and can be summarized like this for analysis… Dimension Fact Dimension Dimension

  13. Dimensional Data and the Data Cube …or it can be expanded in detail like this so that data mining (complex statistical analysis) can be done. Sales Fact Store Dimension Product Dimension Time Dimension

  14. Comparing Operational and Analytical Data Stores

  15. The agenda for the course Weeks 1 through 5 Weeks 6 through 8 Weeks 9 through 13 Data entry Transactional Database Data extraction Analytical Data Store Data analysis Stores real-time transactional data Stores historical transactional and summary data Weeks 14 and 15 Data Visualization

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