Difference between revisions of "OLAP"
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| Line 24: | Line 24: | ||
Updated infrequently, not as large <br /> | Updated infrequently, not as large <br /> | ||
e.g. stores, items, customers, students, courses, webpages, users, advertisers | e.g. stores, items, customers, students, courses, webpages, users, advertisers | ||
| + | * '''Fact table references dimension tables''' | ||
| + | ==== Example ==== | ||
| + | * Fact table | ||
| + | Sales(storeID, itemID, custID, qty, price) | ||
| + | * Dimenstion tables | ||
| + | Store(storeID, city, state)<br /> | ||
| + | Item(itemID, category, brand, color, size)<br /> | ||
| + | Customer(custID, name, address) | ||
Revision as of 04:39, 13 November 2013
Two Types of Database Activity
- OLTP (Online Transaction Processing)
- short transactions
- simple queries
- touch small portions of data
- frequent update
- OLAP (Online Analytical Processing)
- long transactions
- complex queries
- touch large portions of the data
- infrequent updates
Terminologies
- Data Warehousing
Bring data from operational(OLTP) sources into a single "warehouse" for (OLAP) analysis
- Decision Support System (DSS)
Infrastructure for data analysis, e.g., data warehouse tuned for OLAP
Star Schema
- Fact table
Updated frequently, often append-only, very large
e.g. sales transactions, course enrollments, page view
- Dimension tables
Updated infrequently, not as large
e.g. stores, items, customers, students, courses, webpages, users, advertisers
- Fact table references dimension tables
Example
- Fact table
Sales(storeID, itemID, custID, qty, price)
- Dimenstion tables
Store(storeID, city, state)
Item(itemID, category, brand, color, size)
Customer(custID, name, address)