Data warehouse systems offer a way to create data truth in a company. In such an information system, data is not only stored and sorted, but also cleansed and analyzed.
If you haven’t heard of these information systems, check out our article on the subject. Here we explain the features of such a system and how to provide it with data.
All systems follow the same basic structure, which we explain in this article, but can consist of different components. Accordingly, they are typified. This article is about this classification. In the following, we will introduce you to the functionalities of the most popular data warehouse systems.
Table of Contents
Host-Based mainframe warehouse
The Host-Based mainframe warehouse resides on a large-volume database.
In addition to this database, metadata is managed in a central metadata repository. Within this metadata, for example, the information for the documentation of data sources or data translation rules are stored.
In general, three phases run in this information system.
Selections and scrubbing methods take place in the unloading phase. That is, the appropriate data types and data sources are determined here and the data is subsequently error corrected.
In the following transform phase the data are translated into a suitable form. Here also already the rules for the access and the storage are specified.
In the final Load phase, the preprocessed data set is moved into tables.
Host-Based LAN data warehouse
• extract information from a variety of sources and support multiple LAN based warehouses
• data delivery can be handled either centrally or from the workgroup environment
• size depends on the platform
Multi-Stage Data Warehouses
• staging of the data multiple times before the loading operation into the data warehouse
→finally to departmentalized data marts
Stationary Data Warehouse
• data is not changed from the sources
• customer is given direct access to the data
Distributed Data Warehouses
• two types of distributed data warehouses and their modifications for the local enterprise
warehouses which are distributed throughout the enterprise and a global warehouses
• Activity appears at the local level
• Bulk of the operational processing
• Local site is autonomous
• Local warehouses also include historical data and are integrated only within the local site
Virtual Data Warehouses
Created in the following steps
• Installing a set of data approach, data dictionary, and process management facilities
• Training end-clients
• Monitoring how DW facilities will be used
• Based upon actual usage, physically Data Warehouse is created to provide the high-frequency results
Need to define four kinds of data
• A data dictionary including the definitions of the various databases
• A description of the relationship between the data components
• The description of the method user will interface with the system
• The algorithms and business rules that describe what to do and how to do it
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