Question

You are the DBA of a multinational company. You have data pertaining to 2 million sales agents who are currently working or have worked for your company. This data includes agents’ contact details, ethnicity, gender, marital status, number of children, education background, sales records, bank account numbers and various leave records. Believing that a model will be useful for the recruitment of new sales agents in the future, you plan to use the existing data to develop a model that predicts sales performance. Discuss any ethical issues that may arise when you handle and

Answer 1

According to the data and requirement, The best suitable model for this will be the Rational model because, in the relational model, data is represented using a set of values over a finite set of data.

For better understand need to follow the following steps:

1) Collect the data on which you want to track ( data on which company performance most based).

2) Make a list of questions regarding your company new requirement skills and then try to predict answers to those questions.

2) Plan for the frequency of skills of agents that make more customers and sales products.

3) Set the variable you want to represent(quarterly, monthly, etc.). Depending on your needs, you may have more than one sales analysis report with different variables.

For basic sales analysis, start with high-level variables like date, location, and salary.

Compile sales data manually or export it from point of sale agent and customer relationship management software into a spreadsheet.

4) Present your data on the graph to view and compare agent performance during the holidays, slow seasons, etc.

To gain a historical perspective of sales performance, you can also consider tracking variables in increments over the life of your business, a product, or a service.

Once you complete your analysis asked some questions and try to get an answer from the graph that makes you more about your new sales agent recruitment.

There are some ethical issues may also arise when handling data:

1) Data mismatch, information incomplete

2) Agent performance appraisals data (if the reason for appraisals not given then we face dilemma to predict the reason for appraisals)

3) Connecting multiple tables based on the correct connection link between various information of sales agent data.