Data Marts

Published on June 2016 | Categories: Documents | Downloads: 20 | Comments: 0 | Views: 172
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Data Marts      A data mart is a smaller, more focused data warehouse. It reflects the business rules of a specific business unit. The data mart does not need to cleanse its data because that was done when it went into the warehouse. It is a set of tables for direct access by users. These tables are designed for aggregation. It typically is not a source for traditional statistical analysis.

Farmers and Explorers     Every corporation has two types of DW users. Farmers know what they want before they set out to find it. They submit small queries and retrieve small nuggets of information. Explorers are quite unpredictable. They often submit large queries. Sometimes they find nothing, sometimes they find priceless nuggets. Cost justification for the DW is usually done on the basis of the results obtained by farmers since explorers are unpredictable.

The Data Warehouse and Data Mining    Data mining does not require the use of a warehouse, but it may be the best foundation for mining. If multiple analyses are run in sequence, the data need to be held constant (as in a DW). In an operational database, data change often. Also important is that the data in the DW is integrated (consistent name, format, etc from various sources) and stable.

Characteristics of a Data Warehouse Subject oriented ± organized based on use Integrated ± inconsistencies removed Nonvolatile ± stored in read-only format Time variant ± data are normally time series Summarized ± in decision-usable format Large volume ± data sets are quite large Non normalized ± often redundant Metadata ± data about data are stored Data sources ± comes from nonintegrated sources Components of the Metadata Transformation maps ± records that show what transformations were applied Extraction history ± records that show what data was analyzed Algorithms for summarization ± methods available for aggregating and summarizing Data ownership ± records that show origin Access patterns ± records that show what data are accessed and how often Data Warehouse Technologies No one currently offers an end-to-end DW solution. Organizations buy bits and pieces from a number of vendors and hopefully make them work together. SAS, IBM, Software AG, Information Builders and Platinum offer solutions that are at least fairly comprehensive. The market is very competitive. Table 2-6 in the text lists 90 firms that produce DW products.

What Exactly is an EIS?

An EIS is a special type of DSS designed to support decision making at the top level of an organization. An EIS may help a CEO to get an accurate picture of overall operations, and a summary of what competitors are doing. These systems are generally easy to operate and present information in ways easy to quickly absorb (graphs, charts, etc.). Design Strategies Top-down DW design ± the data warehouse design is based on the enterprise model itself. It implies a strategic, rather than operational, perspective of the data. Bottom-up DW design ± focuses more on making use of the data available in the current system. This is less effort than the top-down approach, but may end up with a DW that does not satisfy all of the organization¶s information needs.

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