Data Warehousing Overview

INTRODUCTION:

A data warehousing stores large amount of data from current and previous years that has been extracted from different sources. Data ware house is very important for business decision making. Without data warehouse it becomes very difficult to manage large amount of data. in this process data from different sources is extracted filtered, edited, screened, standardized, and integrated so it can be used by manager and other end user for important business analysis. In addition to a relational database, a data warehouse environment includes an extraction, transportation, transformation, and loading (ETL) solution, an online analytical processing (OLAP) engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users. one very important application of data ware housing is data mining. Data mining is the process of identifying relationship among data. We can find hidden, unexpected, useful relationship among data. Since business users can quickly access critical data from a number of sources—all in one place—they can rapidly make informed decisions on key initiatives. They won’t waste precious time retrieving data from multiple sources.

 

CONCEPTUAL VIEW:

As business is becoming more competitive, the business risk needs to be insured. The view of decision making situation is no longer atomic, local and functions but it is scope and content. Using data warehouse you can ask lots of questions like how many customers like to purchase product online etc. Data ware house stores historical data so it plays vital role. The initial step in data warehouse is to collect data from different sources after this the data needs to be validated because only valid data should be entered in data warehouse. Such data set is then consolidated to common references level such as end of month etc.

All these process is handled by middle-ware; it is set of programs which validates the data transfers data to data warehouse.

 

Data Warehousing Overview

 

OLAP:

On-Line Analytical Processing (OLAP) is a category of software technology that enables analysts, managers and executives to gain insight into data through fast, consistent, interactive access to a wide variety of possible views of information that has been transformed from raw data to reflect the real dimensionality of the enterprise as understood by the user.

DATA MART:

A data mart can be imagined as a small store in mall i.e. data ware house is a mall and data mart is store inside mall.

Data mart is a subset of data warehouse it stores specific data. On-Line Analytical Processing (OLAP) is a category of software technology that enables analysts, managers and executives to gain insight into data through fast, consistent, interactive access to a wide variety of possible views of information that has been transformed from raw data to reflect the real dimensionality of the enterprise as understood by the user.

 

DATA WAREHOUSE DEVELOPER:

A data ware house developers are the team to design process to take up data from various sources and make it ready as business data to make important decisions.

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Written by Sourabh Bhunje

Sourabh Bhunje, B.E. IT from Pune University. Currently Working at Techliebe.Professional Skills: Programming - Software & Mobile, Web & Graphic Design, Localization, Content Writing, Sub-Titling etc.http://techliebe.com/about-us

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