Introduction

  • 3 minutes

R is an open-source programming language known for its active user community and wide range of packages. These features enable the quick and effective use of data science techniques. You can use the wpa R package to analyze metrics at a level of detail that isn't included in the out-of-the-box Viva Insights data through Workplace Analytics.

Imagine you're a data analyst on an HR business intelligence team that regularly uses Workplace Analytics with Viva Insights. Specifically, you're most likely using the Power BI templates and dashboards available through the Query designer to analyze how employees collaborate across your organization. You're interested in finding new techniques for advanced analysis and alternatives for visualizing data. You might also like to use tools that are easy to incorporate into a data science workflow. To date, you have been using the available Power BI dashboards for reporting. They're valuable, but you see an opportunity to create more flexible and reproducible analysis by incorporating more advanced analysis techniques.

To enable this flexibility and advanced analysis, you can install R and use the wpa R package to analyze Viva Insights data through the Workplace Analytics app. The package includes multiple functions for advanced analysis and reporting. Including these features in a data science workflow gives you another way to share deep insights about working patterns with organization's leaders.

Learning objectives

In this module, you'll learn to:

  • Explain what the wpa R package is, and how it can be useful when analyzing Workplace Analytics data
  • Install R and set up the wpa R package
  • Validate and explore Workplace Analytics data with the wpa R package
  • Use the functions in the wpa R package to create your own analysis

Prerequisites

  • Familiarity with Workplace Analytics data sources and metrics.
  • Basic knowledge of Workplace Analytics queries and query structure.
  • Basic understanding of data manipulation in R. For this, we recommend reviewing the basic verbs in the dplyr package. dplyr overview