Alteryx for Data Analysis
In this course, we start by explaining how to import different datasets into Alteryx. By using tools such as data selection, comment, and containers, we emphasize the importance of well laid out and correctly labeled workflows.
Joining data is a fundamental data preparation skill, but that doesn’t mean that it’s easy. We’ve configured this course to ensure that the users have a much stronger grasp of this essential skill. This course includes covers the basics of unions, joins, pivoting, and transposing data.
In almost all projects, we’ll need to parse data and perform calculations to facilitate further analysis. In this course we’ll look at the parsing and formula tools available in Alteryx.
Through this course, analysts will learn more advanced techniques for parsing and manipulating data through Alteryx. Analysts are introduced to the concepts of Fuzzy Matching and Regular Expressions through a series of lessons.
Data visualization and geospatial mapping are increasingly popular business tools. In this course, we'll look at how Alteryx can help analysts convert coordinates into recognizable geospatial data for mapping and analysis.
These lessons look at the Alteryx interface tools. You will learn how to design and execute dynamic apps, and create Batch Macros and Iterative Macros. Finally, you will learn how to connect Analytical Applications in series.
In this course, we’ll look at how to apply AB Testing to gain greater insight into customer behavior and improve the customer experience.
In this course, we will cross-reference information on one website with geo-data available through an API from a different source. Through this case study, we will learn how to investigate websites to find relevant information, manipulate this data using Alteryx tools and integrate multiple sources to generate an enhanced dataset.
In this case study course, we'll leverage Alteryx to integrate a range of datasets from advertising service providers with web analytics and e-commerce data. The output is then analyzed in Tableau to develop several dashboards.
This course focusing on the use of linear and logistic regression analysis applied to business use cases. Learn how to deploy and assess the quality of your models and improve their predictive performance.
This course looks at the Alteryx time series tools. You’ll use historic data to make univariate and covariate forecasts, and how to compare forecast outputs. Finally, you’ll learn the merits and downsides of customizing the model.
This course looks at classification models in Alteryx. You’ll use sample data to train and validate a predictive model. You’ll see several techniques, then export the preferred models and fit them to new data.
This course covers two common unsupervised learning techniques that can be deployed in Alteryx. The first is market basket analysis which can be used to understand customer behavior. The other is clustering which is used to find underlying patterns in the data in the form of groups.