Reporting Systems

Reflect on the differences among reporting systems, data mining systems, and Big Data systems. What are their similarities and differences? How do their costs differ? What benefits does each offer? How would an organization choose among them?

Solution

DATA MINING SYSTEM

A data mining system is a hardcore analyst stop. This type of tool is heaven for a data freak. It is used as a machine tool who can tell exactly like a mechanic of a car why a car is running weird. This tool is used by the marketing companies who use it to discover trends and confirm strategies or evaluate performance down to the mini details. The advantage of these systems is that it is a powerful tool which allows slicing and dicing of the data. It offers data manipulation and lets one extract precise information for countless possibilities.

The Data mining tool allows complete, precise analysis. It also allows testing of some hypotheses as well as correlations.

The disadvantage of this tool is that it is very expensive. Setting up of this tool is also quite expensive. The end-user needs to learn it and cannot understand it easily (Larose and Larose).

REPORTING TOOLS

The reporting tool is used to create reports. The report would include comparisons, give performances, and help in guiding the decision process. However, it would not aid in making the changes to the system. The reporting tools use historical as well as a contextual view of the data, and unlike the big data analytics or data mining tools it does not allow slicing or dicing of the data to precise levels.

Its advantage is that it is very simple to use. It tracks down the data in time. And the data sharing is easy. However, the disadvantage is that it does not provide an in-depth analysis and the real-time tracking option is limited.

BIG DATA TOOLS

The big data tools can aid in different ways to the companies and operators. Big Data tools use the process of processing as well as storing and visualizing of the data. It utilizes infrastructural technology to process as well as store and report data. It helps the companies to get the answers to the questions that companies do not know. However, as it sounds, it is not easy to operate and is quite expensive (Nisbet, Miner and Yale).

Work Cited

Larose, Daniel T. and Chantal D. Larose. Data Mining and Predictive Analytics. John Wiley & Sons, 2015.

Nisbet, Robert, Gary Miner and Ken Yale. Handbook of Statistical Analysis and Data Mining Applications. Elsevier, 2017.