Platform Options
Let us now turn our attention to the computing, platforms that are needed to perform the several functions of the various components of the data warehouse architecture. A computing platform is the set of hardware components, the operating system, the network, and the net-work software. Whether it is a function of an OLTP system or a decision support system like the data warehouse, the function has to be performed on a computing platform.
Before we get into a deeper discussion of platform options, let us get back to the functions and services of the architectural components in the three major areas. Here is a quick summary recap:
Data Acquisition - data extraction, data transformation, data cleansing, data integration, and data staging.
Data Storage: data loading, archiving, and data management.
Information Delivery: report generation, query processing, and complex analysis.
We will now discuss platform options in terms of the functions in these three areas. Where should each function be performed'? On which platforms? How could you optimize the functions?
Single Platform Option - This is the Iwo straightforward and simplest option for in implementing the data warehouse architecture. In this option, all functions from the end data extraction to the front-end query processing are performed on a single computing platform. This was perhaps the earliest approach, when developers were implementing data warehouses on existing mainframe, minicomputers, or a single UNIX -based saver.
Because all operations ill the data acquisition, data storage, and information deliver areas take place on the same platform, this option hardly ever encounters any compatibility or interface problems. The data flows smoothly from be to end without any platform-to-platform conversions. No middleware is needed. All tools work in a single com-putting environment.
In many companies, legacy systems are still running on mainframes or minis. Some of these companies have migrated to UNIX-based services and others have moved overt l systems in client/server environments as part of the transition to address the Y2K challenge. In any case, most legacy systems still reside on mainframes, minis or UNIX based servers. What is the relationship of the legacy systems to the data warehouse'? Remember, the legacy systems contribute the major part of the data warehouse data. If there companies wish to adopt a single-platform solution, that platform of choice has to I mainframe, mini, or a UNIX-based server.
If the situation in your company warrants serious consideration of the single-platform option, then analyze the implications before making a decision. The single-platform solution appears to be an ideal option. If so, why are not many companies adopting this option now? Let us examine the reasons.
Let us now turn our attention to the computing, platforms that are needed to perform the several functions of the various components of the data warehouse architecture. A computing platform is the set of hardware components, the operating system, the network, and the net-work software. Whether it is a function of an OLTP system or a decision support system like the data warehouse, the function has to be performed on a computing platform.
Before we get into a deeper discussion of platform options, let us get back to the functions and services of the architectural components in the three major areas. Here is a quick summary recap:
Data Acquisition - data extraction, data transformation, data cleansing, data integration, and data staging.
Data Storage: data loading, archiving, and data management.
Information Delivery: report generation, query processing, and complex analysis.
We will now discuss platform options in terms of the functions in these three areas. Where should each function be performed'? On which platforms? How could you optimize the functions?
Single Platform Option - This is the Iwo straightforward and simplest option for in implementing the data warehouse architecture. In this option, all functions from the end data extraction to the front-end query processing are performed on a single computing platform. This was perhaps the earliest approach, when developers were implementing data warehouses on existing mainframe, minicomputers, or a single UNIX -based saver.
Because all operations ill the data acquisition, data storage, and information deliver areas take place on the same platform, this option hardly ever encounters any compatibility or interface problems. The data flows smoothly from be to end without any platform-to-platform conversions. No middleware is needed. All tools work in a single com-putting environment.
In many companies, legacy systems are still running on mainframes or minis. Some of these companies have migrated to UNIX-based services and others have moved overt l systems in client/server environments as part of the transition to address the Y2K challenge. In any case, most legacy systems still reside on mainframes, minis or UNIX based servers. What is the relationship of the legacy systems to the data warehouse'? Remember, the legacy systems contribute the major part of the data warehouse data. If there companies wish to adopt a single-platform solution, that platform of choice has to I mainframe, mini, or a UNIX-based server.
If the situation in your company warrants serious consideration of the single-platform option, then analyze the implications before making a decision. The single-platform solution appears to be an ideal option. If so, why are not many companies adopting this option now? Let us examine the reasons.
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