OLTP VS OLAP
OLTP (ON-LINE TRANSACTIONPROCESSING) is characterized by a large number of short on-linetransactions (INSERT, UPDATE, DEL...
OLAP (ON-LINE ANALYTICAL PROCESSING) is characterized by relatively low volume of transactions. Queries are often very c...
DATA WAREHOUSING ANDOPERATIONAL DBMS
WHAT IS DATA WAREHOUSING?
DEFINITION: A data warehouse is a copy of transaction dataspecifically structured for querying and reporting. An expande...
NOTHING TO DO WITH WHETHERSOMETHING IS A DATA WAREHOUSE. This definition of the data warehouse focuses ondata storage. A...
WHY DO WE NEED DATA WAREHOUSES? Consolidation of information resources Improved query performance Separate research and...
 The data stored in the warehouse is uploaded from theoperational systems. The data may pass through an operational data...
HOW DO DATA WAREHOUSES DIFFER FROMOPERATIONAL DBMS? Goals Structure Size Performance optimization Technologies used
HOW DO DATA WAREHOUSES DIFFER FROMOPERATIONAL SYSTEMS?Data warehouse Operational DBMSSubject oriented Transaction oriented...
DESIGN DIFFERENCESStar SchemaData WarehouseOperational DBMSER Diagram
FUNCTIONS A data warehouse maintains its functions in threelayers: staging, integration, and access. Staging is used to ...
WHAT IS A DATA WAREHOUSE USED FOR? Knowledge discovery Making consolidated reports Finding relationships and correlatio...
THE END
Oltp vs olap
Oltp vs olap
Oltp vs olap
Oltp vs olap
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Oltp vs olap

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Comparison between OLAP vs OLTP

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Oltp vs olap

  1. 1. OLTP VS OLAP
  2. 2. OLTP (ON-LINE TRANSACTIONPROCESSING) is characterized by a large number of short on-linetransactions (INSERT, UPDATE, DELETE). The main emphasis for OLTP systems is put onvery fast query processing, maintaining dataintegrity in multi-access environments and aneffectiveness measured by number of transactionsper second. In OLTP database there is detailed and currentdata, and schema used to store transactionaldatabases is the entity model (usually 3NF).
  3. 3. OLAP (ON-LINE ANALYTICAL PROCESSING) is characterized by relatively low volume of transactions. Queries are often very complex and involveaggregations. For OLAP systems a response time is an effectivenessmeasure. OLAP applications are widely used by Data Miningtechniques. In OLAP database there is aggregated, historical data,stored in multi-dimensional schemas (usually starschema).
  4. 4. DATA WAREHOUSING ANDOPERATIONAL DBMS
  5. 5. WHAT IS DATA WAREHOUSING?
  6. 6. DEFINITION: A data warehouse is a copy of transaction dataspecifically structured for querying and reporting. An expanded definition for data warehousingincludes business intelligence tools, tools toextract, transform and load data into therepository, and tools to manage and retrievemetadata.
  7. 7. NOTHING TO DO WITH WHETHERSOMETHING IS A DATA WAREHOUSE. This definition of the data warehouse focuses ondata storage. A data warehouse can be normalized ordenormalized. It can be a relational database, multidimensionaldatabase, flat file, hierarchical database, objectdatabase, etc. Data warehouse data often gets changed. And data warehouses often focus on a specificactivity or entity.
  8. 8. WHY DO WE NEED DATA WAREHOUSES? Consolidation of information resources Improved query performance Separate research and decision support functionsfrom the operational systems Foundation for data mining, data visualization,advanced reporting and OLAP tools
  9. 9.  The data stored in the warehouse is uploaded from theoperational systems. The data may pass through an operational data store foradditional operations before it is used in the DW forreporting. Operational DBMS is used to deal with the everydayrunning of one aspect of an enterprise. OLTP (on-line transaction processor) or OperationalDBMS are usually designed independently of each otherand it is difficult for them to share information.
  10. 10. HOW DO DATA WAREHOUSES DIFFER FROMOPERATIONAL DBMS? Goals Structure Size Performance optimization Technologies used
  11. 11. HOW DO DATA WAREHOUSES DIFFER FROMOPERATIONAL SYSTEMS?Data warehouse Operational DBMSSubject oriented Transaction orientedLarge (hundreds of GB up toseveral TB)Small (MB up to several GB)Historic data Current dataDe-normalized table structure(few tables, many columns pertable)Normalized table structure (manytables, few columns per table)Batch updates Continuous updatesUsually very complex queries Simple to complex queries
  12. 12. DESIGN DIFFERENCESStar SchemaData WarehouseOperational DBMSER Diagram
  13. 13. FUNCTIONS A data warehouse maintains its functions in threelayers: staging, integration, and access. Staging is used to store raw data for use bydevelopers (analysis and support). The integration layer is used to integrate data andto have a level of abstraction from users. The access layer is for getting data out for users.
  14. 14. WHAT IS A DATA WAREHOUSE USED FOR? Knowledge discovery Making consolidated reports Finding relationships and correlations Data mining Examples Banks identifying credit risks Insurance companies searching for fraud Medical research
  15. 15. THE END
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