DatatWare Housing

What makes a data warehouse important for a company is its ability to gather information from different parts and then making them a single part of a centralized database. It is a collection of data, which is further used by employees for an easy and smooth working process. Know more about data warehousing by reading the article.

Data warehouse is an asset for an organization because it maintains the efficiency, profitability and competitive graph. A company collects data from sources like inventory manageable, call center, sales leads etc., which is then passed through the Data Life Cycle Management policy. It is this policy of the organization that determines the design and methodology of the data warehouse.

The main motive of a data warehouse is to create front-end analytics that will support the operation staff and other employees of the organization. Here are some of the elements of a data warehouse:

Pre-Data Warehouse

This zone provides data for the data warehousing and the team of designers filters out the data that contains business value for insertion. Operational data is stored in OLTP database, which resides in transactional software applications like supply chain, ERP etc. OLTP's are designed for high transaction speed and accuracy.

It is the metadata that ensures accuracy of data that will be entered into the warehouse. Most of the organizations reduce cost for the ETL stage by opting for a metadata policy.

Data Cleansing

Data cleansing is the extraction, transformation and cleaning process that are done to ensure the quality of the data before it is entered in the warehouse.

Data Repository

Data repository is a database where active data of an organization is stored. It is then optimized for data analysis.

There are two types of data warehouses - ODS and Data Marts. Although data marts are no different from data warehouses in physical terms but they can be smaller and are built on departmental level instead of company level.

One drawback of data warehouse is that it collects data and has older data as well, which means you will not get an up-to-date analysis. Operational Data Stores can be useful when it comes to storing recent data before migrating to the data warehouse.

Front-End Analysis

Front-end application that will be used by employees is the most critical part of a data warehouse. They will use it to extract information and interact with the data stored in the repositories.

Data Mining

It is the discovery of many useful patterns in the data. Data mining is used for analyzing and the classification process.

Data Visualization Tools

These tools are used for displaying the data from the data repository. Designers often combine it with data mining and OLAP tools. The process of data visualization helps users in manipulating data as per its relevancy and pattern.