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What is Bi-directional Extract?In hierarchical, networked or relational databases, the data can be extracted, cleansed and transferred in two directions. The ability of a system to do this is refered to as bidirectional extracts.
This functionality is extremely useful in data warehousing projects.
Data Extraction
The source systems the data is extracted from vary in various forms right from their structures and file formats to the department and the business segment they belong to. Common source formats include flat files and relational database and other non-relational database structures such as IMS, VSAM or ISAM.
Data transformation
The extracted data may undergo transformation with possible addition of metadata before they are exported to another large storage area.
In transformation phase, various functions related to business needs, requirements, rules and policies are applied on them. During this process some values even get translated and encoded. Care is also taken to avoid redundancy of data.
Data Cleansing
In data cleansing, scrutinizing of the incorrect or corrupted data is done and those inaccuracies are removed. Thus data consistency is ensured in Data cleansing.
It involves activities like
- removing typographical errors and inconsistencies
- comparing and validating data entries against a list of entities
Data transformation
This is the last process of Bidirectional Extracts. The cleansed, transformed extracted source data is then loaded into the data warehouse.
Advantages
- Updates and data loading become very fast due to bidirectional extracting.
- As timely updates are received in a useful pattern companies can make good use of this data to launch new products and formulate market strategies.
Disadvantage
- More investment on advance and faster IT infrastructure.
- Not being able to come up with fault tolerance may mean unexpected stoppage of operations when the system breaks.
- Skilled data administrator needs to be hired to manage the complex process.
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