Data warehousing involves the storage of a large quantities of data from one or more disparate sources into central repositories of integrated data in order to ensure safety and accessibility. Data warehousing facilitates data retrieval. Both current and historical data are stored and can be accessed to create analytical reports for knowledge workers throughout the enterprise It is a system used for reporting and data analysis, and is considered a core component of business intelligence.
The term “data warehousing” was coined by Bill Inmon, who first it in the 1970s. In the late 1980s, IBM researchers Barry Devlin and Paul Murphy developed the data warehousing concept, which was intended to provide an architectural model for the flow of data from operational systems to decision support environments. It attempted to address problems associated with this flow, mainly the high cost and the generation of redundancies required to support different decision environments. In larger corporations, it was typical for multiple decision support environments to operate independently. Though each environment served different users, they often required the same data, and the process of gathering, cleaning and integrating data from various sources was often replicated for each environment. Furthermore, operational systems were frequently reexamined as new decision support requirements emerged.
The benefits of data warehousing include:
 The integration of data from multiple sources into a single database and data model so that a single query engine can be used to present data and provide a consolidated perspective across the enterprise.
 Mitigation of the problem of database isolation caused by attempts to run large, long running, analysis queries in transaction-processing databases.
 Maintenance of data history.
 Improvement of data quality.
 Present the organization’s information consistently.
 Restructuring of the data so that it makes sense to users and to streamlining of query performance without impacting the operational systems.
 Add value to operational business applications, such as management of customer relations.
 Facilitating the writing of decision–support queries.
 Disambiguation of repetitive data.
Data warehousing ensures secure data storage and ensures that businesses and government organizations can access data relevant to products and service-users. Specialized tools allow for segregation of frequently used data from idle data in order make data access more efficient. Warehoused data can also be updated efficiently.
Tools that can filter data efficiently and that can be tailored to the needs of the user are required. The following tools are often used for data warehousing.
Ab Initio: Specialized in high-volume data processing applications and enterprise application integration. A free version of this data-warehousing tool (Elementum™) is available.
Codefutures: dbShards, a NewSQL platform based on database sharing is . designed to provide scalability to companies and can be used with traditional database platforms like MySQL and PostgreSQL, thereby avoiding the need to replace existing database engines.
Teradata Integrated Data Warehouses: Feature the ability to integrate data from multiple sources and benefit from Intelligent in-memory processing with a low total cost of ownership, and the ability to be deployed on-premises, with Teradata IntelliCloud in public, private or hybrid cloud environments.
One of the key elements to business success is the ability to respond quickly to market changes and opportunities, which depends on the efficient use of data. Data warehousing is therefore an important consideration for all organizations. Data warehousing allows organizations to protect their data and to make it accessible very efficiently, and ensures savings of both time and money over the long term.
Further reading
1. Dedić, N. and Stanier C., 2016. “An Evaluation of the Challenges of Multilingualism in Data Warehouse Development” in 18th International Conference on Enterprise Information Systems – ICEIS 2016
2. William Inmon. Building the Data Warehouse (2005). John Wiley and Sons
3. Kimball, Ralph and Ross, Margy. The Data Warehouse Toolkit Third Edition (2013) Wiley and Sons.

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