Data Warehousing: Introduction to Data Warehousing   

In the past, most companies or organizations was facing the difficulty in reporting system and managing the large data. Without the good system, these 2 activities can not be done effectively or efficiently.   

Historical data is important for company to do forecasting and to analyze the current strategy compared to previous strategy so the better future strategy can be provided for better company improvement. Data warehousing is a very efficient system for storing information, and it is very useful in recent years as we have entered information era. 

Data warehousing application is a piece of software that provides a user interface for users to add, delete, query and update data. 

This data warehousing system focuses on data storage which is used in particular organization and it is designed to facilitate reporting and analytical activities. It is used to retrieve, collect, and store the data or information periodically from the source systems into a certain categories of data store. Personal computers and mainframes could be some of the source systems for data warehousing. Two categories of data stores include dimensional & normalized data stores.  

Usually data warehousing keeps the data history for years, so it is very useful for the company to efficiently manage the information and do the business analysis by using the information from data warehousing. As data warehousing is very powerful tools to manage a large data and has the ability to analyze the data, it will overcome the system which is not designed to analyze or report the information. By using the data warehouse system, analyzing of data can be done in quite a short time, so the management in a particular organization can quickly take an important decision.  

Building a data warehousing system will be a smart business intelligence solution. To build a useful data warehouse, it is very important to have good knowledge of the data, sound software engineering, stability from source systems, users who want a success and strong executive support. 

Today most data warehouses are used for business intelligence to enhance Customers Relationship Management (CRM) and for data mining. Some are also used for reporting, and some are used for data integration, These usages are all interrelared, for example, business intelligence and CRM use data mining, business intelligence uses reporting, and BI and CRM also use data integration.

Data Warehousing Process  

Data warehousing process include some of these below applications: 

OLTP (Online Transaction Processing) is a source system which is an update online transaction processing application. This OLTP system is used to capture and store business transactions. DSS (decision support system) is an application that issues queries to the read only database. Most organizations have several disparate OLTP/DSS applications such as finance, sales, etc in each several databases. Some problems with several DSS application are time consume for users who wish to access data as they must query several different DSS to find it. Sometimes there is fundamental conflict between DSS such as different code, unit measurement, etc between one DSS to others DSS. 

Integration of the separate source systems using ETL system in data warehousing will be a good solution. Beside data integration, ETL will transform and load the data from various sources into a DDS (dimensional data store). The ETL system is managed and arranged by the control system, based on the sequences, rules, and logic stored in the metadata.  

To monitors the operational activities of the ETL processes and logs their operational statistics, the audit system is used. 

With the integration system, data warehousing system will help users to find the answers to their questions in one place.