Introduction to data warehouse dmbi
- 1. GANDHINAGAR INSTITUTE OF TECHNOLGY Department of Information Technology Introduction To Data Warehouse Group ID: IT_B1_00 Student Name(Enroll No): Shaishav Shah(170120116094) Name of Faculty: Prof. Rahul Vaghela Data Mining & Business Intelligence(2170715)
- 2. What is Data Warehouse? • “A data warehouse is a subject-oriented, integrated, time-variant, and non-volatile collection of data in support of management’s decision-making process.”—W. H. Inmon • Data warehousing: – The process of constructing and using data warehouses.
- 3. Data Warehouse Features 1. Subject Oriented 2. Integrated 3. Time Variant 4. Non-volatile
- 4. Subject-Oriented • Organized around major subjects, such as customer, product, sales, employee. • Focusing on the modeling and analysis of data for decision makers, not on daily operations or transaction processing. • Provide a simple and concise view around particular subject issues by excluding data that are not useful in the decision support process.
- 5. Integrated • Constructed by integrating multiple, heterogeneous data sources – Relational databases, flat files, on-line transaction records. • Data cleaning and data integration techniques are applied. – Ensure consistency in naming conventions, encoding structures, attribute measures, etc. among different data sources. – E.g., Hotel price: currency, tax, breakfast covered, etc.
- 6. Time Variant • The time horizon for the data warehouse is significantly longer than that of operational systems – Operational database: current value data – Data warehouse data: provide information from a historical perspective (e.g., past 5-10 years) • Every key structure in the data warehouse – Contains an element of time, explicitly or implicitly – But the key of operational data may or may not contain “time element”
- 7. Non-volatile • A physically separate store of data transformed from the operational environment • Operational update of data does not occur in the data warehouse environment – Does not require transaction processing, recovery, and concurrency control mechanisms – Requires only two operations in data accessing: • initial loading of data and access of data.
- 8. Data Warehouse vs. Operational DBMS OLTP (on-line transaction processing) OLAP (on-line analytical processing) •Major task of traditional relational DBMS. •Major task of data warehouse system •Day-to-day operations: purchasing, inventory, banking, manufacturing, payroll, registration, accounting, etc. •Data analysis and decision making
- 9. Thank You