Step by Step Tutorials

Exploratory Desktop provides a streamlined experience for Data Wrangling, Visualization & Machine Learning, powered by R.

To help you become most productive for working with any data and gaining deep insights with Exploratory Desktop, we have prepared a set of tutorials. Each tutorial is designed to address a different use case so you don't need to follow any particular order. However, we'd recommend you take a look at 'Quick Start Guide'

Quick Start Guide

• Quick Start Guide

Data Source Type

MongoDB Data

Working with MongoDB can be challenging due to the nature of NoSQL database, which is highly optimized for capturing the data but not for querying or analyzing the data. Unlike relational database or tabular data, the data is often hierarchical and nested and contains the array type of data. With Exploratory, not only can you extract the data from MongoDB quickly, but also you can make such non-tidy (not tabular / not normalized) data to tidy format based on your needs and apply statistical analysis easily. This tutorial walk you through the steps.

• Working with MongoDB Data in Exploratory
• An Introduction to MongoDB Query for Beginners

JSON Data

• Working with JSON Data

Amazon Redshift Database

• Exploratory Data Analysis for Amazon Redshift DB Data in Exploratory

Web Scraping

• Scraping Table Data from Web Sites

Access Log Data

• Analyze Log file with URL Data

Stripe Data

• Importing Stripe Payment Data, Visualize, and Schedule with Exploratory
• Analyzing MRR (Monthly Recurring Revenue) using Stripe Data in R and Exploratory
• Forecasting MRR for Next 12 Months with Stripe Data & Prophet in Exploratory

MailChimp Data

Google Analytics Data

• Analyzing User Conversion Funnel Data from Google Analytics with dplyr

Data Wrangling

• Data Wrangling / Analysis Grammar - Basic
• Working with Text Data
• Working with Date and Time Data
• Creating Buckets or Categories for Numeric Column Values in Exploratory
• Introduction to Join — Bring extra columns from the target in Exploratory
• Introduction to Join — filtering data based on the target data in Exploratory

Analytics / Machine Learning

• An Introduction to Time Series Forecasting in Exploratory
• Text Analysis / Text Mining
• An Introduction to Linear Regression Model in Exploratory
• A Quick Introduction to Logistic Regression in Exploratory
• An Introduction to K-means Clustering in Exploratory
• An Introduction to Anomaly Detection in R with Exploratory
• An Introduction to Survival Analysis Part 1— Survival Curve
• An Introduction to Survival Analysis Part 2 — Survival Model (Cox Regression)
• An Introduction to Extreme Gradient Boosting in Exploratory
• Finding Similarities Among California Counties based on 2016 Election Result with dist, mds, and kmeans in R