This presentation introduces a product of “Easy Analytics”, which combines strengths from both Data Science and Business Intelligence and automates statistical analyses to boost user engagement. The tool generates easy-to-understand insights for HR employees, regardless of their analytical background. Lastly, analyses can be flexibly adjusted to various use cases, content-wise and with respect to the scope of the analysis.

In this presentation you will learn:

• About an approach to create a Power BI dashboard with custom analyses and visuals, from correlation to regression
• How Python integrations can enhance Power BI’s analytical capabilities without scaring people off
• How a Power BI dashboard can be setup for automated driver analyses

• What are the common sources of bias in HR analytics, and how can they be identified and mitigated during the data collection process?
• How can HR professionals ensure that predictive algorithms used for recruitment and performance evaluations are free from gender, racial, or age biases?
• What role does transparency play in the development of fair HR analytics models, and how can organizations ensure stakeholders understand how these models make decisions?
• What are some key fairness metrics or methodologies that can be employed to evaluate the equity and inclusiveness of HR analytics outcomes?
• How can companies regularly audit and update their HR analytics systems to ensure ongoing fairness and compliance with diversity and inclusion goals?