Sample Thesis Paper
In earlier decade, data storage was carried out with a system through which data that had passed a certain age was deleted. A first in first out mechanism would ensure this function. More recently, the significance of data, regardless of its age, has jumped exponentially (Hammergren and Simon 2009). While older data storage system would delete older data in an attempt to save resources and increase response time, modern day data warehousing systems bring about this efficiency through advanced data storage, analysis and retrieval techniques. The objective has moved from achieving optimum performance, to a continuous process of customization and modernization to go beyond optimum performance.
In the modern day world of excessive data making it next to impossible for timely processing, analysis and reporting, data warehousing allows the systematic and structured storage of data to facilitate these three functions (Ponniah 2001). What makes data warehousing a significant concept in data storage is the fact that it is used in cases where the volume of data has reached unmanageable extents and more data is accumulating. In such cases, the mismanagement of data can create long delays when specific data is required for analysis. It is because of this reason that the science of data warehousing incorporates the complex intricacies of data classification, data storage and data retrieval. Data Warehousing has become an integral part of the IT architecture of modern day organizations (Humphries, Hawkins and Dy 1999).