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operational systems vs data warehousing

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Operational systems vs data warehousing : we started talking about data warehousing concept. If you already have some working experience of Operational data (Production data) , you must be wondering how different will be the Data warehouse data compared to operational Data . So in below tutorial , we will give some basic comparison of Data warehouse data and Operational data.

operational systems vs data warehousing

operational systems vs data warehousing

How is Data warehouse different from Operational data?

The data warehouse is distinctly different from the operational data used and maintained by day-to-day operational systems. Data warehousing is not simply an “access wrapper” for operational data, where data is simply “dumped” into tables for direct access.

Check here for Data warehouse concepts

Operational systems vs Data warehousing

The fundamental difference between operational systems and data warehousing systems is that operational systems are designed to support transaction processing whereas data warehousing systems are designed to support on-line analytical processing (or OLAP, for short).

Based on this fundamental difference, data usage patterns associated with operational systems are significantly different than usage patterns associated with data warehousing systems. As a result, data warehousing systems are designed and optimized using methodologies that drastically differ from that of operational systems.

OPERATIONAL DATA DW DATA
application oriented  subject oriented
detailed summarized  otherwise refined
accurate, as of the moment of access  represents values over time, snapshots
serves the clerical community  serves the managerial community
is be updated frequently  is not updated (Frequently)
run repetitively and non reflectively  run heuristically
requirements for processing understood before
initial development
 requirements for processing not completely
understood before development
compatible with the Software Development Life
Cycle
completely different life cycle
performance sensitive (immediate response
required when entering a transaction)
 performance relaxed (immediacy not required)
accessed a unit at a time (limited number of data
elements for a single record)
 accessed a set at a time (many records of many data
elements)
 transaction driven  analysis driven
 control of update a major concern in terms of ownership  control of update no issue
 high availability  relaxed availability
 managed in its entirety  managed by subsets
 nonredundancy  redundancy is a fact of life
 static structure; variable contents  flexible structure
 small amount of data used in a process  large amount of data used in a process

Check here for Data warehouse architecture

So in above small tutorial , we have gone through the same basic difference between data warehouse data and operational data.

The Author

Alisha Lamba

Hello Friends , I am Alisha Lamba .I love to write article on latest technologies like Informatica , ETL , data warehouse , SQL-PL SQL
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