Explain ODS?

Operational data store is a part of data warehouse. This is maintained only current transactional data. ODS is subject oriented, integrated, volatile, current data.

Difference between OLTP and OLAP?

OLTP : IT is a Online Transaction Processing. This is maintained current transactional data. That means insert, update and delete must be fast.

OLAP(On-line Analytical Processing)): It deals with Historical Data or Archival Data. Historical data are those data that are archived over a long period of time.

Data from  OLTP are collected over a period of time and store it in a very large database called Data warehouse.

Type's of ETL's Used to Implementing Data Acquisition ?

There are 2 types of ETL's Used to implement Data Acquisition.

   1.Code Base.
   2.GUI Based ETL.

1.Code based ETL:
         An ETL application can be developed using some programming language such as SQL ,PL/SQL.

      Ex:- a.Oracle sql loader
             b.Sas based
             c.Sas access
             d.Tera Data load utilities
                               BTDQ(batch tera data query)
                                Fast load
                                Multi load
                                Fast export
                                            etc.....

2. GUI Based ETL:(we used such method in informatica)
              An ETL Application can be designed using simple graphically use interface ,Point & Technology.
             
     Ex:-a. Informatica(informatica corporation)
            b.Data storage(IBM Corp.)
            c.Data service(SAP)
            d.SSIS(Microsoft)-SQL Server Integration Services (SSIS)

Bill Inmon vs. Ralph Kimball

Kimball -Let everybody build what they want when they want it, we'll integrate it all when and if we need              to.(BOTTOM-UP APPROACH).
            Pros: fast to build, quick ROI, nimble
           Cons: harder to maintain as an enterprise resource, often redundant, often difficult to
           integrate data marts.

Inmon - Don't do anything until you've designed everything.(TOP-DOWN APPROACH)
             Pros: easy to maitain, tightly integrated
             Cons: takes way too long to deliver first projects, rigid

                                    There is no right or wrong between these two ideas, as they represent different data warehousing philosophies. In reality, the data warehouse systems in most enterprises are closer to Ralph Kimball's idea. This is because most data warehouses started out as a departmental effort, and hence they originated as a data mart. Only when more data marts are built later do they evolve into a data warehouse.

What is Data mart?

A subset of data warehouse is called Data mart.

Types:

  A. Dependent data mart :It gets data from datawarehouse.

  B. Independent data mart:it does not get data from datawrehouse.

Difference between data warehouse and an operational database ?

operational database:

1.It is designed to support business transnational processing.

2. Data is volatile .

3.Current Data .

4. Design for Running the business .   

5. Normalization .

6. More joins .

 Data warehouse :

1.It is designed to support Decision Making  process.
2. Data is Non-volatile .
3.Historical Data .
4. Design for Analyzing  the business .
5. De-Normalization .
6. Few joins .

What is Data warehousing ?

Data warehousing concepts (FAQ’s)
1)      What is Data warehouse?
Data warehouse is relational database used for query analysis and reporting. By definition data warehouse is Subject-oriented, Integrated, Non-volatile, Time variant.

Subject oriented     : Data warehouse is maintained particular subject.like HR,Sales,Loan ,etc.
Integrated               : Data collected from multiple sources integrated into a
                                   user readable unique format.
Non volatile             : Maintain Historical date.
Time variant            : data display the weekly, monthly, yearly.