Rethinking Big Data and Analytics

This 5 minute vlog post examines the types of data available for analysis.

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.