Machine Learning Use Case: Employee Flight Risk

Contributed Talk | Day 2 | 1:30 pm | 40 Minute Duration | Grand Gallery c
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Machine Learning Use Case: Employee Flight Risk

Contributed Talk | Day 2 | 1:30 pm | 40 Minute Duration | Grand Gallery c

Developing a data-driven organization can be both an intimidating and exciting undertaking. Where do you begin, with what data and at what scale? Many organizations have had success by starting with small analytic projects; projects that have a known track record. Predicting employee flight risk (turnover) is one such use case. This project is an example of supervised machine learning and begins with data that many organizations readily have available. What about technologies? A relatively new cloud-based technology optimized for machine learning is Azure Databricks. Azure Databricks is a unified analytics platform that provides a collaborative workspace environment for all those involved in the development and management of an analytic pipeline, i.e. data engineers, data scientists. Business users can consume the analytic results with reports produced in Microsoft Power BI. Power BI is a cloud-based business intelligence service optimized for data analysis and data visualization. The presentation will walk through the entire machine learning pipeline steps of ingest, preprocess, model, and share using Azure Databricks and Power BI with an anonymized data set.