05-04-2012, 12:21 PM
THE ADVANTAGES AND DISADVANTAGES OF DATA WAREHOUSES
THE ADVANTAGES AND DISADVANTAGES OF DATA WAREHOUSES.docx (Size: 20.58 KB / Downloads: 39)
Data warehouses are the traditional solution for data integration, and for good reason, but this is becoming increasingly difficult to scale and copy data from multiple data sources in multiple organizations in multiple locations
Data is extracted, transformed from multiple data sources and loaded (ETL) into a separate database, called a data warehouse.
Figure 1: Data warehouse.
Advantages
Data warehouses tend to have a high query success as they have complete control over the four main areas of data management systems:
Clean data
Indexes: multiple types
Query processing: multiple options
Security: data and access
Disadvantages
However, there are considerable disadvantages involved in moving data from multiple, often highly disparate, data sources to one data warehouse that translate into long implementation time, high cost, lack of flexibility, dated information, and limited capabilities:
Major data schema transforms from each of the data sources to one schema in the data warehouse, which can represent more than 50% of the total data warehouse effort
Data owners lose control over their data, raising ownership (responsibility and accountability), security and privacy issues
Long initial implementation time and associated high cost
Adding new data sources takes time and associated high cost
Limited flexibility of use and types of users - requires multiple separate data marts for multiple uses and types of users
Typically, data is static and dated
Typically, no data drill-down capabilities
Difficult to accommodate changes in data types and ranges, data source schema, indexes and queries
Typically, cannot actively monitor changes in data
Benefits of data warehousing:
Some of the benefits that a data warehouse provides are as follows: [2][3]
* A data warehouse provides a common data model for all data of interest, regardless of the data's source. This makes it easier to report and analyze information than it would be if multiple data models from disparate sources were used to retrieve information such as sales invoices, order receipts, general ledger charges, etc.
* Prior to loading data into the data warehouse, inconsistencies are identified and resolved. This greatly simplifies reporting and analysis.
* Information in the data warehouse is under the control of data warehouse users so that, even if the source system data is purged over time, the information in the warehouse can be stored safely for extended periods of time.
* Because they are separate from operational systems, data warehouses provide retrieval of data without slowing down operational systems.
* Data warehouses facilitate decision support system applications such as trend reports (e.g., the items with the most sales in a particular area within the last two years), exception reports, and reports that show actual performance versus goals.
* Data warehouses can work in conjunction with and, hence, enhance the value of operational business applications, notably customer relationship management (CRM) systems.
Disadvantages of data warehouses:
There are also disadvantages to using a data warehouse. Some of them are:
* Over their life, data warehouses can have high costs. The data warehouse is usually not static. Maintenance costs are high.
* Data warehouses can get outdated relatively quickly. There is a cost of delivering suboptimal information to the organization.
* There is often a fine line between data warehouses and operational systems. Duplicate, expensive functionality may be developed. Or, functionality may be developed in the data warehouse that, in retrospect, should have been developed in the operational systems and vice versa.