13.2: Concise Summary

Last updated
Save as PDF

Page ID: 93732

\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

In today’s life, data is everywhere and a part of everything. Data is generated whenever you make a purchase, browse the internet, watch a video, visit a web page, or see an ad. That data is collected by your internet service provider, the browser you use, and the web pages you visit. Once all the data is collected, it is stored in data warehouses. These data warehouses manage and maintain the data, storing it in a format that is easily accessible and searchable. The ease of access makes the data easier to use for analysis and comparison.

Data warehousing is an extremely important component of modern business, forming the technical backbone of any given company. Data warehouses are used to store, manage, and access the data that the companies use. Data warehouses process many different types of data, varying from purchase data to internet ad data. Data warehouses operate with the same general structure. The data sources put the data into the warehouse system, and the users access the warehouse through the user level. The warehouse system allows for both the data sources and the users to access the data, helping to resolve some of the information gap between user and source. Keeping track of all this data requires a particular setup in order to be efficient.

Data warehouses are created in a very particular way so that users and data sources can interact with it at the same time. The physical structure of data warehouses consists of a series of computers connected together in such a way so that they share storage space, allowing them to distribute the data for easier access and storage. This system of distributed storage allows for the users to access the data at the same time as the data sources, in addition to having multiple users able to access the data simultaneously. These data warehouses also make it easier to combine multiple data sets into one place, sorting the data sets into a format that is easily searchable and accessible.

While data warehouses are useful systems, allowing users to collate data and search it to be processed, implementing a data warehouse is a very big project. Creating a data warehouse requires a lot of time, money, and resources in order to do properly. A company will have to pay for the computer hardware and networking as well as having to pay employees or contractors to set up the hardware. Once the hardware is set up, the company has to pay their employees to set up the system before it can be used. This results in a time span where they are paying for a system that is not providing any return until it is complete. Depending on the size of the warehouse, this can result in loss of profit versus the cost of set up.

Data warehouses are an exercise in cost-benefit analysis in most situations, usually ending up being more beneficial in the long run. The utility of a system that automatically sorts the data stored within based on input criteria is quite valuable. Once the data warehouse is set up, it ends up resolving a lot of problems that come from not having the sorted collection of data. It allows for employees across the company, and across the country, to access the same data and collaborate in the data analysis. The collaboration ends up saving the company time and effort, eventually resulting in more work done for less effort. All in all, data warehouses expand the availability of data and make data manipulation significantly easier. Data warehouses are a necessity for large companies that is costly to set up in the short term but is well worth the effort in the long term.