A data warehouse is a centralized database used for reporting and data analysis. It integrates data from multiple sources and stores current and historical data to assist management decision making. A data warehouse transforms data into timely information. It allows users to access specific types of data relevant to their needs through smaller data marts. While data warehouses provide benefits like increased access, consistency and productivity, they also present challenges such as lengthy data loads and compatibility issues.

1. DATA WAREHOUSING
A TALK BY, B.R.KARTHIK SRINI
II CSE A

2. WHAT IS A DATA WAREHOUSE??

3. WHAT IS A DATA WAREHOUSE??
➤A data warehouse is an appliance for storing and analysing data, and reporting.
➤Central database that includes information from several different sources.
➤Keeps current as well as historical data.
➤Used to produce reports to assist in decision-making and management.

4. “Type a “Data Warehouse is a subject oriented,
integrated, time-variant and non-volatile
collection of data in support of management’s
decision making process.” – W. H. Inmon

5. WHAT IS DATA WAREHOUSING?

6. WHAT IS DATA WAREHOUSING?
A process of transforming data
into information and making it
available to users in a timely
enough manner to make a
difference
Data
Information

7. WHY DATA WAREHOUSING? & WHERE?

8. WHY DATA WAREHOUSING? & WHERE?

9. WHY DATA WAREHOUSING? & WHERE?

10. WHY DATA WAREHOUSING? & WHERE?

11. DATABASE VS DATA WAREHOUSE

12. DATABASE VS DATA WAREHOUSE
Database
➤ Transaction Oriented
➤ For saving online bargain data
➤ E-R modeling techniques are
used for designing
➤ Capture data
➤ Constitute real time information
Data Warehouse
➤ Subject oriented
➤ For saving historical data
➤ Data modeling techniques are
used for designing.
➤ Analyze data
➤ Constitute entire information
base for all time.

13. DATA MART

14. DATA MART
➤ Contains a subset of the data stored in the data warehouse that is of interest to a specific
business community, department, or set of users.
➤ E.g.: Marketing promotions, finance ,or account collections.
➤ Data marts are small slices of the data warehouse.
➤ Data marts improve end-user response time by allowing users to have access to the
specific type of data they need to view.
➤ A data mart is basically a condensed and more focused version of a data warehouse.

15. DATA WAREHOUSE VS DATA MART

16. DATA WAREHOUSE VS DATA MART
DATA WAREHOUSE
➤ Holds multiple subject areas
➤ Holds very detailed information
➤ Works to integrate all data
sources
➤ Does not necessarily use a
dimensional model but feeds
dimensional models
DATA MART
➤ Often holds only one subject area- for
example, Finance, or Sales
➤ May hold more summarized data
(although many hold full detail)
➤ Concentrates on integrating
information from a given subject area
or set of source systems
➤ Is built focused on a dimensional
model using a star schema

17. THE TIER ARCHITECTURE

19. ADVANTAGES & DISADVANTAGES
OF DATA WAREHOUSING

20. ADVANTAGES
➤ Enhances end-user access to a wide variety of data.
➤ Increases data consistency.
➤ Increases productivity and decreases computing costs.
➤ Is able to combine data from different sources, in one place.
➤ It provides an infrastructure that could support changes to data and replication of the
changed data back into the operational systems.

21. DISADVANTAGES
➤ Extracting, cleaning and loading data could be time consuming.
➤ Problems with compatibility with systems already in place e.g. transaction processing
system.
➤ Providing training to end-users, who end up not using the data warehouse.
➤ Security could develop into a serious issue, especially if the data warehouse is web
accessible.

22. APPLICATIONS OF DATA
WAREHOUSING

23. APPLICATIONS OF DATA WAREHOUSING
Industry Application
Finance Credit card Analysis
Insurance Claims, Fraud Analysis
Telecommunication Call record Analysis
Transport Logistics management
Consumer goods Promotion Analysis

24. CONCLUSION

25. CONCLUSION
Data Warehousing is not a new phenomenon. All large organisations already have data
warehouses, but they are just not managing them. Over the next few years, the growth of data
warehousing is going to be enormous with new products and technologies coming out
frequently. In order to get the most out of this period, it is going to be important that data
warehouse planners and developers have a clear idea of what they are looking for and then
choose strategies and methods that will provide them with performance today and flexibility
for tomorrow.

26. THANK YOU
A
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