Data Mining on Business, OJC TelU & UTP
Data Mining on Business is a new method that can be used by some corporations to learn about their target customers’ needs and interests. The topic of the online joint class between Telkom University and Universiti Teknologi Petronas (UTP) Malaysia, held on Friday, July 7th, 2023, is Data Mining on Business. This latest collaboration has brought us to the world of business, where data mining is one of the useful techniques with multiple regression and predictive analytics. We’ve been given a warm welcome by Universiti Teknologi PETRONAS, and we also learned so many things from our wonderful speakers, Assoc Prof. Angelina Prima Ph.D. from Telkom University and Assoc Prof. Dr. Maran Marimuthu from Universiti Teknologi PETRONAS.
Data Mining on Business Highlight
Th followings are main points for Data Mining on Business discussed in this online joint class:
- Predictive Analysis
- Data Exploration
- Dimension Reduction
- Association Rules
- Regression Modelling-Metric & Non-Metric Variables
As previously mentioned that Data Mining on Business introduces us to multiple regression and the challenges of using many predictors from Data Mining on Business and variable selection algorithms. According to the speakers’ presentation on Data Mining on Business class, the most popular model for making predictions in Data Mining on Business is multiple linear regression, which is applicable to numerous predictive modeling situations.
In addition, Predictive Analytics or Analysis is the main formula in Data Mining on Business. It’s so important for the predictive goal that even if Data Mining on Business drops the first assumption and allows the noise to follow an arbitrary distribution, these estimates are very good for Data Mining on Business. Even if the other assumptions for the data mining on business are violated, it is still possible that the resulting predictions are sufficiently accurate and precise for the purpose of the data mining on business they are intended for.
These explanations and methods were taught by Assoc Prof. Dr. Maran Marimuthu, who also taught the students some programming code for the data mining on business. Meanwhile, Assoc Prof. Angelina Prima, Ph.D is more focused on the output, or result, of making progress in the data mining on business. Based on Dr. Angelina’s explanation, Data Mining on Business also requires High Precision, Low Simplicity, and generalization until various unique models can be done for the business itself. Again, not to go too far from the main formula, predictive analytics also requires multivariate statistics and forecasting, so the result and the outcome can be perfect.
In conclusion, we could really use data mining for our corporation’s or company’s needs; it has a lot of benefits that could boost our business and help us reach our target. Hopefully this session will be a new insight, and knowledge for the students. See you in the next class!
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