Understanding Of Data Warehousing

Understanding Of Data Warehousing

Understanding Of Data Warehousing

What is a data warehouse is important to a company's ability to gather information from various parties and in fact a part of a centralized database. This is a collection of data, which is still used by employees of a simple process and good work. More information about the storage of data by reading the article.

data warehouse is an asset to an organization because it sets the efficiency, profitability and competitive graphic. A company collects data from sources such as inventory management, call center, sales leads, etc., which is then passed through the data life cycle management policies. It is the policy of the organization design and methodology of the data warehouse provides.

The main reason for a data warehouse is to create tests that the front service staff and other employees of the organization to support. Some elements of a data warehouse:

Data warehouse pre-

This area provides information for data warehousing and the design team to the commercial data a value for insertion contains filter. The operational data are stored in the OLTP database, which resides in software applications such as transactional supply chain, ERP, OLTP, etc. are designed for high transaction speed and accuracy.

It is the metadata that ensures the accuracy of the data will be included in the magazine. Most organizations the cost phase ETL choose a policy of metadata.

Data Cleansing

Data Cleansing is the extraction, transformation and cleansing process that has been made to ensure the quality of the data before it is recorded in the warehouse.

Data Repository

data repository is a database containing the details of an organization is stored. It is optimized for data analysis.

There are two types of data warehouses - ODS and Data Marts. While the data marts are not different from data warehouses in physical terms, but they can be smaller and are built on the departmental level rather than enterprise level.

A drawback of the data warehouse is that data and more data, also collects, which means there's no room for analysis to date. Operational data stores can be useful when it comes to current data store before the transition to the data warehouse.

Front-End Analysis

front-end application that will be used by the employees is the most critical component of a data warehouse. They will use to retrieve information and interact with data stored in the depots.

Data Mining

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

Data visualization tools

These tools are used to transfer data from the data repository. Designers often combine data mining and OLAP tools. The process of data visualization allows users to manipulate data according to its relevance and design.

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