In layman terms - Datawarehouse is also a Database with additional features to reduce Drawbacks.
Data Warehouse
Earlier, Database was collection of data represented by E.R. Diagram – Entity Relationship Diagram where
data was arranged in pre-defined diagrams. Big amount of data was tough to manage and analyze efficiently in E.R. Diagrams.
Drawbacks of E.R. Diagram:
1. E.R. Diagram based architecture leads to lots of joints resulting in increase of time to process request.
2. Databases are not designed to store old data.(historical data)
3. Data warehouse is designed such that protocol doesn’t take long time to serve a request.
Data Warehouse is basically information storage area.
Proper definition for Data Warehouse:
Data warehouse is a collection of data which is subject oriented, integrated, time variant and non volatile. It is used for the purpose of assisting the group of super users who are part of DSS (Decision Support System).
DSS is collection of tools, resources, manpower and collection instructions on how to enhance business in appropriate manner.
Subject Oriented: A data warehouse based on department or module. Unlike Database where all module’s data are kept together.
Time Variant: Data value varies based on time factor.
Non-volatile: Data is not going to change over time
Integrated: Integrating data from different data sources.
We can create n number of Data warehouse based on client requirement.
Earlier to DW, the analysis was done on OLTP server because there was neither a need nor a budget allocated for analysis of historical data.
The analysis happening on mission critical cases is also one reason why the industry felt need for DW.
Also, in transaction server - data is prone to change all the time unlike DW server data once stored will never change.
Other reasons for need of DW include resource and memory intensive searches and analysis in OLTP started affecting day to day operations. It was not possible to do both analysis and transactions in the same server at the same time.
DW is still developing and there are more and more DW tools available in market. More than 50 tools available as of now.
The operation of DW in SAP is done through SAP BW.
New Age Terms:
EAI (Enterprise Application Integration)
SAP BIIP (Integrated Planning).
Middle Ware Technologies: SAP XI, BizTalk, TIBCO, MQ Series, Web Methods
Data Warehouse
Earlier, Database was collection of data represented by E.R. Diagram – Entity Relationship Diagram where
data was arranged in pre-defined diagrams. Big amount of data was tough to manage and analyze efficiently in E.R. Diagrams.
Drawbacks of E.R. Diagram:
1. E.R. Diagram based architecture leads to lots of joints resulting in increase of time to process request.
2. Databases are not designed to store old data.(historical data)
3. Data warehouse is designed such that protocol doesn’t take long time to serve a request.
Data Warehouse is basically information storage area.
Proper definition for Data Warehouse:
Data warehouse is a collection of data which is subject oriented, integrated, time variant and non volatile. It is used for the purpose of assisting the group of super users who are part of DSS (Decision Support System).
DSS is collection of tools, resources, manpower and collection instructions on how to enhance business in appropriate manner.
Subject Oriented: A data warehouse based on department or module. Unlike Database where all module’s data are kept together.
Time Variant: Data value varies based on time factor.
Non-volatile: Data is not going to change over time
Integrated: Integrating data from different data sources.
We can create n number of Data warehouse based on client requirement.
Earlier to DW, the analysis was done on OLTP server because there was neither a need nor a budget allocated for analysis of historical data.
The analysis happening on mission critical cases is also one reason why the industry felt need for DW.
Also, in transaction server - data is prone to change all the time unlike DW server data once stored will never change.
Other reasons for need of DW include resource and memory intensive searches and analysis in OLTP started affecting day to day operations. It was not possible to do both analysis and transactions in the same server at the same time.
DW is still developing and there are more and more DW tools available in market. More than 50 tools available as of now.
The operation of DW in SAP is done through SAP BW.
New Age Terms:
EAI (Enterprise Application Integration)
SAP BIIP (Integrated Planning).
Middle Ware Technologies: SAP XI, BizTalk, TIBCO, MQ Series, Web Methods
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