Data Mining and Business Analytics

Posted by Seyed Ziae Mousavi Mojab

Dec 10

Editor's note: Seyed Ziae Mousavi Mojab is a computer science student from Wayne State University in Detroit, MI and currently in ISM 7505: Inbound Information Technology

Data Mining and Business Analytics: Developing a model to solve a typical business problem

  • Would you like to know more about the customers’ past experience?
  • Would you like to predict their future behavior with high accuracy?
  • Is the market changing so rapidly, that you feel you are in need of more intelligent reports, and accurate information for a quick and strategic decision?

If you are a decision maker inside a company, and you are concerned about your business' most valuable asset, “customers”, and their relationship, you may need some evolutionary techniques.

One of the main techniques to explore and extract useful information from a huge amount of data is called Data Mining. In general, Data mining is defined as: “the computational process of discovering patterns in large data sets (big data) involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems." (Wikipedia)

Data Mining can also be considered as a systematic information processing technique to discover valuable knowledge in data. Using statistical methods, or genetic algorithms, data sets can be automatically searched for statistical anomalies, patterns and rules. Data Mining is not something new, and statisticians, for many years, have manually explored, and mined their data. However, the new technologies are helping us use more robust and efficient algorithms to simplify and automate the whole mining process. Using Data Mining techniques, you can adjust your final model to accurately predict the unknown data.

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Topic Categories: Data Mining, business analytics

Inbound Information Technology: Personas of Prospective Students

Posted by John H. Heinrichs

Jun 22

As the Information Systems Management (ISM) department focuses on educating “students for careers within the information profession,” an important learning outcome is to “utilize the most relevant information technologies”.  One of the information technologies available for visualizing and understanding data is data mining.  Coupling this information technology with the Inbound Information Technology techniques enables ISM to better understand their prospective students.  Using data mining technology enables ISM inbound marketers to answer questions such as:

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Topic Categories: Excel, Inbound Information Technology, Data Mining

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