An Overview of Data Warehousing and OLAP Technology

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Presentation transcript:

An Overview of Data Warehousing and OLAP Technology

Outline Introduction Architecture of data warehousing Back end tools OLTP applications vs. OLAP applications Architecture of data warehousing Back end tools Conceptual model Front end tools Some examples

Introduction (OLTP applications) OLTP applications typically automate clerical data processing tasks. such as order entry and banking transactions These tasks are structured and repetitive, and consist of short, atomic, isolated transactions. The transactions require detailed, up-to-date data. Consistency and recoverability of the operational database are critical.

Introduction (OLAP applications) OLAP applications are designed for supporting decision making. Historical, summarized and consolidated data are often used. The workload of data warehouses are query intensive with mostly ad hoc, complex queries that access millions of records. Query throughput and response times are critical.

Introduction (problem statement) Given that operational databases, trying to execute complex OLAP queries would result in unacceptable performance. Decision support requires data that might be missing from the operational databases. Decision support requires consolidating data from many heterogeneous sources. Supporting the multidimensional data models and operations requires special data organization, access methods and implementation methods. =>Data Warehouse

Architecture of data warehouse

Back end tools Data extraction Data clearing Load Refresh ODBC, Oracle Open Connect, and Sybase Enterprise Connect, etc. Data clearing Tools that help to detect data anomalies and correct them. Load Tools that help to load data into the warehouse. Refresh Refreshing a warehouse consists in propagating updates on source data.

Conceptual model

Database design MOLAP Array ROLAP Star schema

Warehouse servers Index structures Materialized views Bit map indices, join indices Materialized views Transformation of complex SQL queries Parallel processing SQL extensions Aggregate function Reporting features Multiple group-by Comparisions

Front end tools Spreadsheet Query/Reporting Data mining tools Operations for spreadsheet Pivoting Rollup Drill-down Slice_and_dice Query/Reporting Data mining tools

Examples Oracle Informix Sybase …