What is Data Warehousing ?
- Like
a conventional ware house where excess inventory is stored for easy
access of items and can be requested by users on as-need-be basis; the
digital information is stored in data warehouses(DW).
- The same concept of storing data and its availability as a conventional physical warehouse can crystallize the concept.
- DW
is the channelizing of data from various sources into one streamlined ,
easy to manipulate fashion where data can be used to determine trends
from the past. Generally accepted methods of accessing data include
queries,analysis and reporting. Since a single database is created ,
there can be numerous sources to input data.It is the large database in
the end that is manipulated by users to gather required information.
- Companies depend on data warehousing to analyze trends over time. The Top Data Warehousing Companies use data warehousing to learn more about the day-to-day operations but more importantly analyze trends over time but its main functionality lies in facilitating strategic planning resulting from long-term overviews.
- The
data is mostly read-only since its objective is present an
overview-like reporting.If any changes are required to the data stored
in in the DW, a query needs to be generated.
-
DW is specifically designed to assist in decision making for the management that depicts a collective picture of the everything related to business at a single given time.
Where is Data Warehousing and Data Mart being used today?
Examples include:
The
companies use the data to research the customers preferences
extensively and to sell/utilize the information gathered third-parties
who then use this information for future product development and/or to
up-sale their existing products. The digital information brings
companies like the above mentioned, very close to understanding its
customers and clients alike which is immensely beneficial. | Data Warehouse vs Data Mart
Data Warehouse | Data Mart | A data structure that is optimized for distribution | A data structure that is optimized for access |
It collects and stores integrated sets of historical data from
multiple operational systems and feeds them to one or more data marts. | It is designed to facilitate end-user analysis of data. | It may also provide end-user access to support enterprise views of data | It typically supports a single, analytic used by a distinct set of workers | Associated with enterprise-wide business processes and decisions | Targets a specific business segment of that enterprise |
| Easier to understand Data Mart as a subset of Data Warehouse but not a universally accepted concept. |
Picture taken from http://en.wikipedia.org/wiki/File:Data_warehouse_overview.JPG
Picture taken from http://data-warehouses.net/architecture/datamarts.html
Key Functions :ETL based Data Warehouse
| Staging Layer | It stores raw extracted data from different sources of data. | | Integration Layer | It
transforms the data from the staging layer while storing it in an ODS (
operational data store) database. It is later stored in an hierarchy or
groups based on priority, called dimensions | | Access Layer | It makes the data accessible to the users to retrieve the necessary data |
Emerging Data Warehousing Strategies
|
|
