Open main menu
Home
Random
Recent changes
Special pages
Community portal
Preferences
About Wikipedia
Disclaimers
Incubator escapee wiki
Search
User menu
Talk
Dark mode
Contributions
Create account
Log in
Editing
Data warehouse
(section)
Warning:
You are not logged in. Your IP address will be publicly visible if you make any edits. If you
log in
or
create an account
, your edits will be attributed to your username, along with other benefits.
Anti-spam check. Do
not
fill this in!
==Variants== ===ETL=== The typical [[extract, transform, load]] (ETL)-based data warehouse uses [[Staging (data)|staging]], [[data integration]], and access layers to house its key functions. The staging layer or staging database stores raw data extracted from each of the disparate source data systems. The integration layer integrates disparate data sets by transforming the data from the staging layer, often storing this transformed data in an [[operational data store]] (ODS) database. The integrated data are then moved to yet another database, often called the data warehouse database, where the data is arranged into hierarchical groups, often called dimensions, and into [[#Facts|facts]] and aggregate facts. The combination of facts and dimensions is sometimes called a [[star schema]]. The access layer helps users retrieve data.<ref name=IJCA96Patil>{{cite journal |url=http://www.ijcaonline.org/proceedings/icwet/number9/2131-db195 |author1=Patil, Preeti S. |author2=Srikantha Rao |author3=Suryakant B. Patil |title=Optimization of Data Warehousing System: Simplification in Reporting and Analysis |journal=IJCA Proceedings on International Conference and Workshop on Emerging Trends in Technology |year=2011 |volume=9 |issue=6 |pages=33β37 |publisher=Foundation of Computer Science}}</ref> The main source of the data is [[data cleansing|cleansed]], transformed, catalogued, and made available for use by managers and other business professionals for [[data mining]], [[OLAP|online analytical processing]], [[market research]] and [[decision support]].<ref>Marakas & O'Brien 2009</ref> However, the means to retrieve and analyze data, to extract, transform, and load data, and to manage the [[data dictionary]] are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition of data warehousing includes [[business intelligence tools]], tools to extract, transform, and load data into the repository, and tools to manage and retrieve [[metadata]]. ===ELT=== [[File:ELT Diagram.png|thumb|244x244px|[[Extract, load, transform|ELT]]-based data warehouse architecture]] [[Extract, load, transform|ELT]]-based data warehousing gets rid of a separate [[Extract, transform, load|ETL]] tool for data transformation. Instead, it maintains a staging area inside the data warehouse itself. In this approach, data gets extracted from heterogeneous source systems and are then directly loaded into the data warehouse, before any transformation occurs. All necessary transformations are then handled inside the data warehouse itself. Finally, the manipulated data gets loaded into target tables in the same data warehouse.
Edit summary
(Briefly describe your changes)
By publishing changes, you agree to the
Terms of Use
, and you irrevocably agree to release your contribution under the
CC BY-SA 4.0 License
and the
GFDL
. You agree that a hyperlink or URL is sufficient attribution under the Creative Commons license.
Cancel
Editing help
(opens in new window)