The Experts below are selected from a list of 33 Experts worldwide ranked by ideXlab platform
J. Anitha - One of the best experts on this subject based on the ideXlab platform.
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Data Warehousing Concept Using ETL Process for SCD Type-2
2013Co-Authors: K. Srikanth, Nistala V. E. S. Murthy, J. AnithaAbstract:SCD type 2 will store the entire history in the dimension table. In SCD type 2 effective date, the dimension table will have Start_Date and End_Date as the fields. If the End_Date is Null, then it indicates the current row. Know more about SCDs at Slowly Changing Dimensions Concepts. The new Incoming Record (changed/modified data set) replaces the existing old Record in target. We will see how to implement the SCD Type 2 Effective Date in informatica. If there are retrospective changes made to the contents of the dimension, or if new attributes are added to the dimension which have different effective dates from those already defined, then this can result in the existing transactions needing to be updated to reflect the new situation. As an example consider the Employee dimension.
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Data Warehousing Concept Using ETL Process For SCD Type-1
2012Co-Authors: K. Srikanth, Nistala V. E. S. Murthy, J. Anitha, M. TechAbstract:A Type 1 change overwrites an existing dimensional attribute with new information. In the customer name-change example, the new name overwrites the old name, and the value for the old version is lost. A Type One change updates only the attribute, doesn't insert new Records, and affects no keys. The new Incoming Record (changed/modified data set) replaces the existing old Record in target. It is easy to implement but does not maintain any history of prior attribute values. Slowly Changing Dimensions (SCDs) are dimensions that have data that changes slowly, rather than changing on a time-based, regular schedule.
K. Srikanth - One of the best experts on this subject based on the ideXlab platform.
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Data Warehousing Concept Using ETL Process for SCD Type-2
2013Co-Authors: K. Srikanth, Nistala V. E. S. Murthy, J. AnithaAbstract:SCD type 2 will store the entire history in the dimension table. In SCD type 2 effective date, the dimension table will have Start_Date and End_Date as the fields. If the End_Date is Null, then it indicates the current row. Know more about SCDs at Slowly Changing Dimensions Concepts. The new Incoming Record (changed/modified data set) replaces the existing old Record in target. We will see how to implement the SCD Type 2 Effective Date in informatica. If there are retrospective changes made to the contents of the dimension, or if new attributes are added to the dimension which have different effective dates from those already defined, then this can result in the existing transactions needing to be updated to reflect the new situation. As an example consider the Employee dimension.
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Data Warehousing Concept Using ETL Process For SCD Type-1
2012Co-Authors: K. Srikanth, Nistala V. E. S. Murthy, J. Anitha, M. TechAbstract:A Type 1 change overwrites an existing dimensional attribute with new information. In the customer name-change example, the new name overwrites the old name, and the value for the old version is lost. A Type One change updates only the attribute, doesn't insert new Records, and affects no keys. The new Incoming Record (changed/modified data set) replaces the existing old Record in target. It is easy to implement but does not maintain any history of prior attribute values. Slowly Changing Dimensions (SCDs) are dimensions that have data that changes slowly, rather than changing on a time-based, regular schedule.
Nistala V. E. S. Murthy - One of the best experts on this subject based on the ideXlab platform.
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Data Warehousing Concept Using ETL Process for SCD Type-2
2013Co-Authors: K. Srikanth, Nistala V. E. S. Murthy, J. AnithaAbstract:SCD type 2 will store the entire history in the dimension table. In SCD type 2 effective date, the dimension table will have Start_Date and End_Date as the fields. If the End_Date is Null, then it indicates the current row. Know more about SCDs at Slowly Changing Dimensions Concepts. The new Incoming Record (changed/modified data set) replaces the existing old Record in target. We will see how to implement the SCD Type 2 Effective Date in informatica. If there are retrospective changes made to the contents of the dimension, or if new attributes are added to the dimension which have different effective dates from those already defined, then this can result in the existing transactions needing to be updated to reflect the new situation. As an example consider the Employee dimension.
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Data Warehousing Concept Using ETL Process For SCD Type-1
2012Co-Authors: K. Srikanth, Nistala V. E. S. Murthy, J. Anitha, M. TechAbstract:A Type 1 change overwrites an existing dimensional attribute with new information. In the customer name-change example, the new name overwrites the old name, and the value for the old version is lost. A Type One change updates only the attribute, doesn't insert new Records, and affects no keys. The new Incoming Record (changed/modified data set) replaces the existing old Record in target. It is easy to implement but does not maintain any history of prior attribute values. Slowly Changing Dimensions (SCDs) are dimensions that have data that changes slowly, rather than changing on a time-based, regular schedule.
M. Tech - One of the best experts on this subject based on the ideXlab platform.
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Data Warehousing Concept Using ETL Process For SCD Type-1
2012Co-Authors: K. Srikanth, Nistala V. E. S. Murthy, J. Anitha, M. TechAbstract:A Type 1 change overwrites an existing dimensional attribute with new information. In the customer name-change example, the new name overwrites the old name, and the value for the old version is lost. A Type One change updates only the attribute, doesn't insert new Records, and affects no keys. The new Incoming Record (changed/modified data set) replaces the existing old Record in target. It is easy to implement but does not maintain any history of prior attribute values. Slowly Changing Dimensions (SCDs) are dimensions that have data that changes slowly, rather than changing on a time-based, regular schedule.
Ia M Oki - One of the best experts on this subject based on the ideXlab platform.
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continuous queries over append only databases
International Conference on Management of Data, 1992Co-Authors: Douglas Terry, David Goldberg, David A Nichols, Ia M OkiAbstract:In a database to which data is continually added, users may wish to issue a permanent query and be notified whenever data matches the query. If such continuous queries examine only single Records, this can be implemented by examining each Record as it arrives. This is very efficient because only the Incoming Record needs to be scanned. This simple approach does not work for queries involving joins or time. The Tapestry system allows users to issue such queries over a database of mail and bulletin board messages. The user issues a static query, such as “show me all messages that have been replied to by Jones,” as though the database were fixed and unchanging. Tapestry converts the query into an incremental query that efficiently finds new matches to the original query as new messages are added to the database. This paper describes the techniques used in Tapestry, which do not depend on triggers and thus be implemented on any commercial database that supports SQL. Although Tapestry is designed for filtering mail and news messages, its techniques are applicable to any append-only database.
