Data Warehouse Origin and History

A Key Concept in Information Systems – Data Warehouse Origin and History

Data warehouse refers to a collection of various data with varying structures. It is a relational database which is structured for analysis and query and not for transaction processing. It normally has historical data derived from data transaction, though it can comprise of data from other sources (Shivtare & Shelar, 1, p.67). Data warehouse was used long before 1990s, though it was first defined in 1991. Its origin was initiated by desire to use data to enhance business competitive advantage. Data warehouse initial users focused on putting related data together. Although it was used long before its definition, most of enterprises got to understand it years after its introduction. According to Kim (5, p.39), majority of enterprises came to realize that the data they had at their disposal were essential assets, which when leveraged properly can offer them competitive advantage, in the late 1990s. These enterprises also realized that their data have been stored in disparate systems, and to be able to run applications, the data had to be integrated. The need for enterprise data integration offered a motivation to data warehouse creation. The initial step towards data warehousing was the data fixed presentation. The objective was to develop a system on top of controlling and automation applications.The original warehouse was founded on IBM Ireland or Wal-Mart, who defined the data warehouse (Maslankowski, 4, p.43).

Current Use of Data Warehouse

Data warehouse refers to a system which cleans, extracts, source and confirms data into a dimensional data store, and then implements and supports analysis and querying for the decision making purpose. Data warehouse is said to offer business conditions coherent picture at a specific point of time, it is thus utilized for effectual decision making process. Data warehouse entails the development of system which assists the data extraction in flexible ways. It integrates multiple data stores and this information is utilized by the managers for improved decision making. Environment of data warehousing comprises of the relational database extraction, client analysis tools, engine of online analytical processing (OLAP), loading and transformation (Joseph, 2, p. 329). 

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Data warehouse is used in different private and governmental organizations. It is used in healthcare organization to store data which are later used to evaluate the healthcare efficiency in offering quality care. This information assists in making decisions on the aspects to be improved on to enhance the general performance, for instance in reducing rate of medical errors, patient waiting time, and cases of readmission. Healthcare data in this case is collected using electronic medical records (EMR), they are then stored and integrated in data warehouses, where they are later extracted for analysis and decision making (Evans, Lloyd & Pierce, 3, p.190). Data warehousing concept is also applied in the government services. Data warehouse is used in the storage of data in e-government system that is used to collect different kinds of data from the citizens. The data warehouse is then used by the government decision makers to analyze different situations in the country using different queries. The queries complex analysis results are then used in making decisions that are likely to change life of the citizens in a great way (Arora & Gupta, 7, p.28).

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Common Attitudes toward the Data Warehouse

Data warehouse is highly embraced by almost all organizations that need to store huge volumes of data from different sources. Data warehouse is highly supported and embraced for its ability to organize data in a manner that it can be easily retrieved and analyzed. It is highly supported by business or organization managers and data analysts, who highly depend on it to make important decisions in an organization. Majority of data warehouse users are highly satisfied by its operability and level of efficiency, in data manipulation and analysis (Chen, Soliman, Mao & Frolic, 8, p.106).

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Similar to other data users, I am also highly satisfied by data warehouse functionality and effectiveness in enhancing data manipulation and analysis for effective decision making. However, I am always concerned about data warehouse security and how lack of security can impact the credibility, confidentiality, integrity and reliability of the stored data. Although I highly embrace data warehouse concept and its role in enhancing data analysis and decision making, I am always keen on the employed security measures and importance of sealing all security loopholes.

Fundamental Strengths and Weaknesses of Data Warehouse

Data warehouse is associated with a number of advantages and disadvantages. One of the main warehouse disadvantages is inability to totally ensure clean data. Although data warehouse has a data cleansing mechanism to ensure only clean data is obtained, it is considerably hard to attain perfection, since data quality and cleanliness is also determine by the data source. Another disadvantage is that it is considerably hard to handle large volumes of data stored in the data warehouse. It is always hard to cope with large volumes of data, especially in a warehouse that holds a lot of outdated data. The main advantage of data warehouse is that it enhances business intelligence since data warehouse features facilitate data analysis, ensuring that the organization only practices informed decision making. Data warehouse also enhances timely data access as the organization data are integrated in a single warehouse. It also facilitates increased system performance and query enhancing data analysis and decision making (Cuzzocrea, Bellatreche and Song, 6).

Prevailing View that Experts Hold about the Likely Future of the Data Warehouse

Data warehouse has been experiencing a lot of advancements since it was defined. This includeshardware advancement, which provided powerful processing power, and enough data storage space. Ithas also empowered by provision of advanced data warehouse appliances that ensure certified configuration and creating a balance between services, software and hardware. There has been further advancement of database storage technology which enhances easy access and data querying. Today, the data warehouse has advanced to be integrated to big data technology which adds to the warehouse data holding capacity. The analysis simply demonstrates the growing and advancement of data warehouse technology in the industry.

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Shivtare and Shelar (1)thus believe that data warehouse will continue to grow to enhance its storage ability and performance power in terms of data ease of accessibility and analysis.Cuzzocrea, Bellatreche and Song (6) believe that there will be high level of integration of the big data and data warehouse with intention of creating a more liable data management system with limited challenges. According to Maslankowski (4), the world is growing in terms of data production and need of data storage, especially with advance use of social media platform, this will create demand for large, secure and easily accessible data storage technologies, an aspect increase chances of integrating cloud technology to data warehouse technology in the future


Data warehouse technology has been of great importance in enhancement of data management and data analysis. Its main purpose is to promote decision making process. Although data warehouse has both advantages and disadvantages, its advantages surpass the disadvantages, and hence it has been highly embraced. Data warehouse has highly managed to blend well with the new technology and hence it demonstrates strong ability to survive future technological advancements.

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