7ISAS REPORT

Coordinator : Nguyen Tien Cuong

Group : 3

Student : Nguyen Tuan Anh

Do Thi Hoa

Nguyen Nam Hoang

Nguyen Duy Hai

Quarter : 2

Data Warehouse

Microsoft

Oracle

IBM

SAP

Microsoft Data Warehouse

INTRODUCTION

A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but can include data from other sources

Data warehouses separate analysis workload from transaction workload and enable an organization to consolidate data from several sources.

In addition to a relational database, a data warehouse environment can include an extraction, transportation, transformation, and loading (ETL) solution, online analytical processing (OLAP) and data mining capabilities, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users

CONCEPT

These terms are used as follows

Subject Oriented : The data in the data warehouse is organized so that all the data elements relating to the same real-world event or object are linked together.

Integrated : Though the data in the data warehouses is scattered around different tables, databases or even servers but the data is integrated consistently in the values of variables, naming conventions and physical data definitions.

Nonvolatile: Data in the data warehouse is never over-written or deleted - once committed, the data is static, read-only, and retained for future reporting.

Time – variant : The changes to the data in the data warehouse are tracked and recorded so that reports can be produced showing changes over time.

FUNCTION

A data warehouse must develop a process to collect the pure raw materials and then continually repackage them to serve evolving business initiatives.

Data warehouses must be built, managed, and delivered. We do not want to change the technology so it’s important to get it right.

A long feature set is not beneficial if development is onerous and cycle turnaround times are long and costly.

Each new initiative that a data warehouse serves should be treated as a project within a program.

The data warehouse process is an information product process. We must establish the guiding principles and champion, architect, deliver, and support iterations.

The data warehouse engine is the company’s information factory and it should have high reliability.

MANAGING A DATA WAREHOUSE

Microsoft SQL Server 2005 provides a manageable, scalable data warehouse platform. With several enhancements in SQL Server 2005, Microsoft enables Information Technology departments to productively manaSge their growing data volumes along with the rapid increase in usage of the data warehouse.

SQL Server database management system

Accessible techniques to manage deployment

Delivering a data warehouse

Interactive data access

SQL Server Analysis Services

Reporting Services

CONCLUTION

Through the technology underlying the Microsoft Data Warehousing Framework and the remarkable progress in Microsoft SQL Server 7.0, Microsoft is working to reduce complexity, improve integration, and lower costs associated with storage data.

Customers investing in data storage technology based on Microsoft can be assured that they are creating applications with the best possible economic considerations, while maintaining full scalability and reliability of their systems.

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