The organisation you work for is experiencing a problem with high staff turnover. The board would like to better understand the reasons for the high levels of staff turnover, the impact on the business, and what they should do about it. They have asked you to analyse the past year of employee data, and to prepare a report that addresses these issues.The report should draw on the analysis of the data as well as the wider literature on the topic.
The analytics tasks that you need to complete are described below, along with the suggested structure of the report.
You have been provided with one year of data extracted from the organisations human resource information system. The data set includes variables relating to individual employee characteristics, performance, and attrition. A data dictionary is provided on canvas.
Using the data provided carry out the following analytics tasks for inform your report:
1.Identify and address any data quality issues in the dataset.
2.Using Tableau, carry out an exploration of the data. Produce at least 4 standalone visualisations as well as an HR dashboard. The visualisations and dashboard should provide insights for senior HR managers, and potentially for other business users. Include any relevant visualisations in your final report.
3.Import the data into KNIME in preparation for the development of a predictive workflow.
4.Carry out any additional descriptive tasks and data pre-processing that is necessary.
5.Split the data into a training and test set.
6.Produce at least one predictive model.
7.Evaluate the performance of the model.
8.Include appropriate details of the model and its performance in the report.
The written report should cover the following areas (but is not limited to these):
1.Introduction and background to the problem: consider the business problem or question to be solved through the analysis. Briefly review any literature that may help to inform your analysis.
2.Methodology: a description of the analytics tasks undertaken and reasons why these were used.
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