Business Intelligence Buyer's Guide

The Best DataCamp Data Analytics & Visualization Courses for 2023

The Best DataCamp Courses for Data Analytics and Visualization

The Best DataCamp Courses for Data Analytics and Visualization

A directory of the best DataCamp training courses for data analytics and visualization, compiled by the editors at Solutions Review.

SR Finds 106Data analytics is a data science. The purpose of data analytics is to generate insights from data by connecting patterns and trends with organizational goals. Comparing data assets against organizational hypotheses is a common use case of data analytics, and the practice tends to be focused on business and strategy. Data analytics deals less in AI, machine learning, and predictive modeling, and more with viewing historical data in context.

With this in mind, the editors at Solutions Review have compiled this list of the best DataCamp courses for data analytics and visualization. DataCamp’s mission is to “democratize data skill for everyone” by offering more than 350 different data science and analytics courses and 12 distinct career tracks. More than 2,000 companies, 3,000 organizations, and 8 million users from 180 countries have used DataCamp since its founding. DataCamp’s entire course catalog is interactive which makes it perfect for learning at your own pace.

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The Best DataCamp Courses for Data Analytics and Visualization

TITLE: Introduction to Power BI

OUR TAKE: This training, according to DataCamp, provides students with a “360 degree overview” of how to explore and use Power BI to build impactful reports. It includes 6 hours of video content, 19 videos, and 56 unique exercises.

Description: In this course, you’ll go from zero to hero, as you discover how to use this popular business intelligence platform through hands-on exercises. You’ll first learn how to confidently load and transform data using Power Query and the importance of data models, before diving into creating visualizations using Power BI’s drag-and-drop functionality. You’ll also learn how to drill-down into reports and make your reports fully interactive. Lastly, you’ll level-up your skills using DAX formulas (Data Analysis Expressions) to create customized calculated columns and fields to better analyze your data.


TITLE: Introduction to Tableau

OUR TAKE: This beginner-level training features 10 projects. Instructor Charlie Walker is a KPMG and E&Y veteran specializing in financial analysis, analytics, and forecasting.

Description: You’ll learn how to navigate Tableau’s interface and connect and present data using easy-to-understand visualizations. By the end of this training, you’ll have the skills you need to confidently explore Tableau and build impactful data dashboards. This module features 29 videos and 70 exercises, and should take around 4 hours to complete. Chapter 1, Getting Started with Tableau, is currently free.


TITLE: Data Analysis in Excel

OUR TAKE: Learn how to analyze data in Excel through 4 hours of interactive video content and 48 unique exercises. The first chapter of this training, Exploring Data, is free. Nearly 80,000 DataCamp students have used this module.

Description: In this course, you’ll develop employable analyst skills as you learn how to use time-saving keyboard shortcuts, convert and clean data types including text, times, and dates, and build impressive logic functions and conditional aggregations. Through hands-on practice, you’ll learn over 35 new Excel functions, including CONCATENATE, VLOOKUP, and AVERAGEIF(S), and work with real-world Kickstarter data as you use your new-found Excel skills to analyze what makes a successful project.


More “Top-Rated” DataCamp paths: Data Analysis in Spreadsheets

TITLE: Data Visualization for Everyone

OUR TAKE: This course offers an introduction to data visualization beginning with visualizing distributions. Students should expect to spend 2 hours on this training by watching two hours of video content and 43 exercises.

Description: In this course, you’ll learn how to choose the best visualization for your dataset, and how to interpret common plot types like histograms, scatter plots, line plots and bar plots. You’ll also learn about best practices for using colors and shapes in your plots, and how to avoid common pitfalls. Through hands-on exercises, you’ll visually explore over 20 datasets including global life expectancies, Los Angeles home prices, ESPN’s 100 most famous athletes, and the greatest hip-hop songs of all time.


More “Top-Rated” DataCamp paths: Data Visualization in R, Data Visualization in Spreadsheets, Introduction to Data Visualization in Python

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