Your SlideShare is downloading. ×
Data extraction, transformation, and loading
Data extraction, transformation, and loading
Data extraction, transformation, and loading
Data extraction, transformation, and loading
Data extraction, transformation, and loading
Data extraction, transformation, and loading
Data extraction, transformation, and loading
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Data extraction, transformation, and loading

223

Published on

Data extraction in data warehouse

Data extraction in data warehouse

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
223
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
5
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. *
  • 2. * *Survey broadly all the various aspects of the data extraction ,transformation and loading(ETL)functions *Examine the data extraction function,its challenges,its tecniques,and learn how to evaluate and apply the tecniques *Discuss the wide range of tasks and types of the transformation function
  • 3. *Understand the meaning of data integration and consolidation *Percieve the importance of data load function
  • 4. *ETL functions reshape the relevant datd from the source systems into useful information to be stored in the data warehouse. *Without these function,there would be no strategic information in the data warehouse. *If the source data is not extracted correctly,cleansed,and integrated in the proper formats,query processing,the backbone of the data warehouse,could not happen.
  • 5. * *The architecture divided into three functional areas such as data acquisition, data storage and information delivery. *ETL encompass the area of data acquisition and data storage. *These are back-end processes that cover the extraction of data from the source systems. *Next, source data into the exact formats and structures appropriate for data storage in data warehouse. *After data transformation of the data, moving data into the data warehouse repository.
  • 6. * *Data extraction-why not extract all of operational data and dump into data warehouse? *Avoid creating

×