Reference no: EM132966233

Question 1:

A successful data analytics project is the combined result of the various software/tools used as well as the domain knowledge and reasoning skills of the data analyst.

Discuss the key message in the above statement based on your knowledge of "business analytics" in general. Support your discussion by providing specific examples from the application of the different techniques (supervised and unsupervised).

Question 2:

As a data analyst, you should perform data exploration, visualization, and pre-processing before proceeding directly to applying any high-powered predictive technique.

a) Using these techniques (i.e., decision tree, logistic regression, artificial neural network), explain how data exploration, visualization, and pre-processing steps impact your data analysis process and your potential findings from these techniques. Be sure to provide sufficient details and examples in your explanation.

b) Explain how your approaches and methods differ when applying data exploration, visualization, and pre-processing methods for numerical versus categorical variables in your data. Use specific and relevant examples in your explanation

Question 3:

One of the major challenges in data mining (machine learning) techniques is choosing the final model(s) and the best result(s). This is in contrast to traditional techniques such as linear programming and integer programming which often give you one best result if there is any feasible solution. Discuss the unique characteristics, advantages and disadvantages of data mining (machine learning) techniques in comparison to those traditional techniques such as linear programming and integer programming. Use related concepts as well as sufficient examples to expand on your discussion

Question 4:

The potential benefits of Business Analytics is not limited to mainstream profit-making sectors and businesses. Several public or government sector applications have been documented in practice.

a) Discuss with sufficient examples some of the opportunities and potential areas of business analytics applications in the public/government sector. What are the potential benefits?

b) Compared to the private sector, what do you think could be the unique challenges (constraints) for successful business analytics practices in the public/government sector?

Please answer the above questions.