|
|
 |
|
| |
|
|
| |
by Exforsys.com
|
|
print article · comment on article
|
|
| |
previous |
page 2 of 3 |
next |
|
| |
|
|
| |
Optimized for validation of incoming data during transactions; uses validation data tables.
Supports thousands of concurrent users.
Objectives of a Data warehouse and Data flow
The primary objective of data warehousing is to provide a consolidated, flexible meaningful data repository to the end user for reporting and analysis. All other objectives of Data warehousing are derived from this primary objective. The data flow in the warehouse also is determined by the objectives of data warehousing.
The data in a data warehouse is extracted from a variety of sources. OLTP databases, historical repositories and external data sources offload their data into the data warehouse. Achieving a constant and efficient connection to the data source is one of the objectives of data warehousing. This process is known as Data Source Interaction.
The data extracted from diverse sources will have to be checked for integrity and will have to be cleaned and then loaded into the warehouse for meaningful analysis. Therefore, harnessing efficient data cleaning and loading technologies (ETL—Extraction, Transformation and Loading) to the warehousing system will be another objective of the data warehouse. This process is known as Data Transformation service or Data preparation and staging.
The cleaned and stored data will have to be partitioned, summarized and stored for efficient query and analysis. Creating of subject oriented data marts, dimensional models of data and use of data mining technologies would follow, as the next objective of data warehousing. This process is called Data Storage |
|
| |
|
|
| |
previous |
1·2·3 |
next |
|
|
