The Definitive Guide to Data Analytics

A complementary 7-session introduction to analytics

The Definitive Guide to Data Analytics Training Series

Analytics (sometimes referred to as data science) is the study of patterns in data for the purpose of identifying trends, finding correlations, and optimizing decisions. Put another way, analytics is the science of fact-based decision making. Analytics has grown in popularity for more than 20 years. As computing power has improved, organizations have hired more and more employees to help them optimize decisions using data. Many people inclined toward math, science, or coding enjoy spending their workday looking for trends and relationships in data. 

The Definitive Guide to Data Analytics training series provides an overview of the analytics landscape and introduces some commonly used analytics tools. Each session is comprised of a video seminar, including hands-on application, on a specific analytics tool. We highly recommend applying the concepts alongside the training. The series requires no prior knowledge of analytics; happy learning!

If you need help troubleshooting code, project advice, or personalized career advice, consider booking a 1-hour analytics consultation with an analytics expert. You’ll be amazed by what we can accomplish in just 1 hour!

If your organization would like customized analytics training, you can learn more about our analytics & leadership training service here.

Watch below or watch The Definitive Guide to Data Analytics playlist on YouTube. You might also enjoy the Analytics and Data Science Career Path playlist, the Analytics and Data Science Techniques playlist, or the Data Analyst and Data Scientist Project Walkthroughs playlist.

 

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Getting started with analytics is a challenge in itself. Doing it alone can be nearly impossible. If you'd prefer live and personalized training on these and more advanced concepts, Value Driven Analytics is your robust, affordable, and timely source for analytics projects, trainings, and transformation.

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