Alteryx for Beginners - Master Alteryx

Filter data with the filter tool in Alteryx (basic and custom), deduplicate using the unique tool, and sample with the sample tool, including group by and sort to refine datasets.

Learn to blend data with join and union tools, align by specific fields or record position, and output left, right, joint data streams.

Learn to summarize and group data with Alteryx using the summarized tool and group by to compute totals, averages, and counts, then pivot with crosstab and transpose for flexible reports.

Explore basic Alteryx functions using the formula tool to create and modify columns, apply string and numeric operations, and use record ID and UID functions, rounding, and random numbers.

Explore Alteryx basic functions and conditional formulas to classify apps as paid or free, apply multi-conditional scoring to ratings, and assign score categories.

Explore the switch conditional function in Alteryx, create case-based content codes, test for null or empty values, and convert between string and numeric data types with practical examples.

Learn to parse and format dates with the date time tool, converting strings to date time and extracting year and month, plus add and diff date operations.

Learn how to parse concatenated data using the text to columns tool, splitting by delimiters like the pipe symbol into columns or rows, and rename fields dynamically to align headers.

Learn how to replace or append data in Alteryx using the find and replace tool, mirroring the vlookup function in Excel, with anchors, field targeting, and optional append behavior.

Explore how to apply a single expression across multiple fields with the multi field formula tool, replace nulls with zeros, and use multi row formula for row-wise calculations in Alteryx.

Build an end-to-end Alteryx workflow by joining movie, ratings, director, and actor data, then clean, transform, and prepare the blended dataset for output.

Discover basic tips and tricks to streamline your Alteryx designer workflows, from canvas setup and grid alignment to favorites, annotations, containers, wire management, and keyboard shortcuts.

Learn to visualize data in Alteryx by using the table tool, basic and pivot tables, and group by to create report-ready, per-month views with bar graphs.

Explore how to add context with the report text tool, choose text modes, and build interactive charts and crosstabs to compare monthly sales and branch income.

Organize report objects with the join multiple and layout tools to place bar and pie charts beside the title and table. Render the layout to a PDF for easy sharing.

Convert standard workflows into analytic apps or macros, design user interfaces with file browse and list box tools, and publish to server or gallery for end users.

Learn how to create and configure standard macros in Alteryx to automate and reuse workflows, including building macro inputs, outputs, and testing with a sample address cleansing workflow.

Learn to work with spatial data—points, lines, and polygons—and convert coordinates to spatial objects using the create point tool, then build routes and polygons with poly build.

Learn to create and analyze trade areas around stores using the trade area tool, measure radii, eliminate overlaps, and compute distances and nearest customers with Alteryx spatial analytics.

Explore how spatial objects relate using Alteryx's spatial process and spatial match tools to combine, cut, and intersect trade areas, and identify customers within mall trade areas.

Explore three analytics types—descriptive, predictive, and prescriptive—and learn to prepare data with Alteryx tools, check data quality, and generate descriptive statistics and an interactive dashboard.

Explore non-hierarchical k-centroid clustering to segment supermarket customers by proximity to centroids, using z-score standardization and k-means to identify four clusters.

Explore the k-nearest neighbor algorithm to classify data by proximity using Euclidean distance. Build a fruit dataset workflow that standardizes features and reveals predicted fruit names.

discover market basket analysis to identify items bought together and boost profits with cross selling. structure data and apply apriori rules with mb rules tool, aided by mb inspect tool.

Explore how predictive analytics uses historical data and logistic regression to classify outcomes with a sigmoid curve and assess model performance.

Learn linear regression as a predictive model for continuous outcomes, using age, BMI, children, smoker, and region to estimate insurance charges with a 70/30 train-test split.

Explore tree-based models, including decision trees, forests, and ensemble methods, and learn how splitting, pruning, and metrics like Gini and information gain shape iris classification.

Discover how random forest uses bagging on bootstrapped samples and random feature selection to overcome overfitting and provide stable, accurate predictions.

Celebrate the journey and highlight what you learned about the data integration and analytics tool in Alteryx. Invite questions and anticipate hearing more about this tool in the coming years.