Introduction
Source:.github/analyst_guide_intro.md
Welcome to the Analyst Guide of the vivainsights R package. This document will guide you through the installation process, explain the package functionality and structure, and get you comfortable with some common functions for analysis.
Before we begin…
Make sure you have: 1. Analyst access to Viva Insights 2. R installed in your local device.
An IDE is optional, but we recommend either RStudio Desktop or VS Code.
Why use R for Viva Insights?
There are multiple reasons:
- Cutting edge data science: R is an open-source language that is known for its active user community and a wide range of packages that together enable the quick and effective implementation of data science techniques.
- Reproducibility: Code-based workflows help facilitate reproducible analysis, which is the notion that analysis should be built in a way that is replicable by others. R as a tool promotes this good practice.
- Efficiency / scalability: R scales relatively well in the context of large datasets. The application of functions and automated processes also help cut down routine analysis time
- Integration: If you already use R as part of your analysis toolkit, adopting this package as part of the workflow will be seamless and easy
- Extensibility: One of the most appealing feature of R is the access it offers to a wide range of packages. For instance, clustering and text mining can be done very easily as part of a R workflow – which are both available in this package
Guide contents
This guide is organized in the following key sections:
- Getting Started: This section contains the detailed installation instructions, and a general overview of how functions work.
Ready to go?
Let’s begin with the Getting Started section.