MSAS : Microsoft Data Warehousing Overview
Modern day enterprises believe that mission critical decisions should be information based. Vast information repositories and historical data available with them need to be analyzed and emerging patterns examined before any decisions are taken. Data warehousing and business intelligence solutions were looked upon as means of achieving this purpose. This need triggered off a proliferation of data warehousing and business intelligence solutions in the market. Initially these solutions were scattered, disparate and focused on specific areas of Data warehousing such as Extraction, Transformation and Load (ETL) solutions at one end and analysis and reporting tools at the other end. OLAP solutions were developed independently and data mining required the deployment of a separate tool. Integration of these various facets of Data warehousing was attempted by large organizations with huge hardware, software and manpower resources to spare. Small and medium enterprises found it impossible to even consider the possibilities of data warehousing in the face of the huge outlays required. It was in this environment that Microsoft entered the market with its integrated data warehousing and business intelligence package –the SQL Server 7.0.
Significantly Microsoft attempted to create an environment for data warehousing called Microsoft data warehousing framework which includes the following functions.
1. Providing access to data from a variety of sources.
2. Building data warehouses and data marts.
3. Transforming data and populating data warehouses and data marts.
4. Creating cubes and storing cubes for client applications
5. Providing access to OLAP cubes for client applications.
6. Providing tools to manage the data warehouse
7. Storing and providing access to meta data.
The SQL Servers released by Microsoft provide for the following tools for building and managing data warehouses.
1. OLE DB for access to data from a variety of sources
2. The Enterprise manager for building data warehouses and data marts
3. DTS for transforming data and populating data warehouses and data marts
4. OLAP services for creating cubes and storing cube data in a relational or multidimensional format.
5. The PivotTable services for client access to cube data
6. English query for natural language access to data .
7. The SQL server database management tools.
8. The repository for storing metadata.
Apart from this Microsoft created what is known as the “Microsoft Data Warehousing alliance”. This is a group of companies, who have joined with Microsoft in supporting this framework for data warehousing. These companies provide tools that work with the Microsoft data warehousing framework. The Alliance partners are many, but a few names are listed under to give an idea of the kind of tools the alliance is developing.
• AppsCo’s Software Limited has developed a tool called AppMart which automates the process of creating data marts.
• DWSoft has created a software called DWGuide. This tool provides a user friendly way to access Microsoft repository.
• Data Junction has created some of the most widely used data transformation tools. These include Data Junction, Cambiro, DJEngine, Custom database Interface SDK, Streaming Data SDK and Data Junction Extraction Language(DJXL).
• Informatica has produced a set of data transformation tools for rapid development. These include PowerCenter, Powermart, Business Components, Power Connect and PowerPlugs.
Microsoft’s SQL Server 2000 is described as the “most comprehensive offering to the data warehousing ecosystem. Microsoft leverages all SQL server based technologies to deliver a comprehensive business intelligence platform with advance data warehousing techniques, analytic functionality, excellent performance and scalability across platforms. The server includes a high performance relational database, OLAP tools, data mining tools, Data transformation services including ETL tools, Meta data services and the English Query. In marketing this server Microsoft focused upon pushing business intelligence to the edge of the enterprise, making it pervasive and more reachable to all levels and types of users. The entire package was dealt out with the well proven Microsoft strategy of fast implementation, ease of learning and use, low cost and high value and fast return on investment.
The entire technology of the SQL Server 2000 was built on in-house technological strengths. Partnerships were used to create a large base of specialized business intelligence tools and applications to support the platform. They were harnessed to simplify and accelerate the adoption of the technology and also make the resources easily accessible to a large number of users.
The Microsoft Data warehousing platform is built on SQL Server technology which was the backbone of the .NET servers. It maintained total control on design, development and deployment of the server and provided an array of application interfaces built on flexible and extensible object oriented component model. These interfaces provide access to all Business intelligence resources with the flexibility and control to address any application requirement. The historical problem of scalability of Microsoft servers was overcome by architectural improvements. It also received a boost from the fast SMP hardware that came in around this time. Today, the server offers a range of services that cater to the low, middle and high ends in terms of capacity and scalability.
