Data Profiling

Data Profiling:

This is a very important activity mostly performed while collecting the requirements and the system study. Data Profiling is a process that familiarizes you with the data you will be loading into the warehouse/mart. In the most basic form, data profiling process would read the source data and report on the

BI Explanation

Business Intelligence (BI):

Business Intelligence (BI) is a generic term used for the processes, methodologies and technologies used for collecting, analyzing and presenting business information. 

       

ETL Explanation

Extract Transform Load (ETL)

The back-end processes involved in collecting data from various sources, preparing the data with respect to the requirements and loading it in the warehouse/mart.
             

Different OLAP's

Online Analytical Processing (OLAP):

Online Analytical Processing (OLAP) is the approach involved in providing analysis to multidimensional data. There are various forms of OLAP namely

ODS

Data Modeling And Normalization

Data Modeling:

This activity is performed once we have understood the requirements for the data warehouse/mart. Data modeling refers to creating the structure and relationship of the data for the business rules defined in the requirements. We create the conceptual model followed by logical model followed by physical model. Here we see a progression in the level of detail as we proceed toward the physical model.

Data Mart

Data Mart

When we restrict the scope of a data warehouse to a sub set of business process or subject area we call it a Data Mart. Data Marts can be stand-alone entities, built from warehouses or be used to build warehouse.
     

Enterprise Data Warehouse (EDW)

Benefits of Data Warehouse

Top Five Benefits of a Data Warehouse:

 

Staging Area (Data Ware House)

What is Staging area why we need it in DWH?

If target and source databases are different and target table volume is high it contains some millions of records in this scenario without staging table we need to design your informatica using look up  to find out whether the record exists or not in the target table since target has huge volumes so its costly to create cache it will hit the performance.

Difference Between Datamart and Data Ware House

Difference Between OLTP and OLAP

Data Mining

Dimensional Modeling

Dimensional modeling (DM) is the name of a set of techniques and concepts used in data warehouse design. Dimensional modeling always uses the concepts of facts (measures), and dimensions (context).

Data Ware House Schemas

Schema:

A schema is a collection of database objects, including tables, views, indexes, and synonyms. You can arrange schema objects in the schema models designed for data warehousing in a variety of ways.

Data Ware House Architectures

Data warehouses and their architectures vary depending upon the specifics of an organization's
situation. Three common architectures are:
 

• Data Warehouse Architecture (Basic)
• Data Warehouse Architecture (with a Staging Area)
• Data Warehouse Architecture (with a Staging Area and Data Marts) 

Data WareHouse Definition

A Data Warehouse (DW) is a database used for reporting. The data is offloaded from the operational systems for reporting. The data may pass through an operational data store for additional operations before it is used in the DW for reporting.