A Practical Guide to Alteryx for Data Science & Analytics

Master data management to prepare and clean data, aligning 80 percent effort with 20 percent analysis, and avoid garbage in garbage out by automating with Alteryx.

Use the FBI crime data as a practical dataset to illustrate real-world data cleaning challenges and the steps to prepare 2015 and 2016 data for analysis.

Save your Alteryx workflow and use the Browse tool to assess data quality. Identify issues like leading spaces, trailing spaces, and data type mismatches, and learn to rename columns.

Learn how to use the select tool in Alteryx to identify and change data types, rename fields, and reorder columns for efficient data cleansing and analysis.

Learn to cleanse data in Alteryx by using auto and select tools, trim spaces, remove bad values, and apply filters to create a consistent, analysis-ready dataset.

Walk through cleaning a 2016 practice dataset in Alteryx, removing punctuation, applying filters to enforce 2016 data, and trimming outliers to ready data for analytics.

Learn why it is important to manage your data, gain skills to understand, assess quality and data types, clean and wrangle data for data science.

Learn data wrangling in Alteryx by combining 2015 and 2016 datasets, applying joinery strategies, transforming data, and building custom formulas for analytics.

Master data joinery by using join and union tools to combine datasets across years, rename fields with dynamic rename, and prepare clean, analysis-ready data.

Create new calculations in Alteryx with formula 2 to compute crime rates per 100k and apply them across multiple fields using multi-field formulas.

Explore Alteryx transformation tools—summarize, group by, transpose, cross tab, and running total—to wrangle long and wide data and join results across years like 2015 and 2016.

Master data wrangling by joining and transforming data, creating new columns and formulas, and mixing tools to enhance functionality before analytics and reporting.

Explore the fundamentals of data analytics, including data, methodologies, statistics, machine learning, and how to create visualizations, geo analytics with shape files, and automated reporting in Alteryx.

Explore Alteryx custom visualizations and insights by building interactive charts, including pie and scatter plots, and refine the reporting tool for clear crime statistics analysis.

Explore spatial analysis with geographic coordinates, shapefiles, and join tools to analyze state borders, calculate areas, crime per square mile, and centroid-based trade areas.

Learn to build automated reports in Alteryx by using filters, union, and overlays to combine maps, charts, and tables into a single polished output.

Learn to integrate R script and Python in Alteryx, importing and exporting data, reading tables into data frames, and executing transformations within a workflow.

Explore key takeaways in data analytics by slicing datasets, creating interactive visualizations, analyzing spatial data, and automating analytics to generate a final report from each workflow run.

Recap the core data science workflow from data management to analytics, highlighting import, clean, wrangle, and transform steps. Build a rock solid foundation for insights, conclusions, and recommendations.

Celebrate your achievement in this practical guide to Alteryx for data science and analytics, as the instructor invites you to apply your newfound skills and share feedback for future courses.