Learn how to do market basket analysis using Alteryx Designer and make data visualizations of your results with Python.

Image for post
Image for post
Photo by Madalin Tudose on Unsplash

Have you ever abandoned a shopping cart in an online store and gotten a reminder email about it later? Your poor digital cart was stranded on a lonely server somewhere. But fear not, readers — we’re not abandoning you! Welcome to the second half of our introduction to market basket analysis.

In the first post, we covered some of the essential concepts behind market basket analysis, so check that out first if you’re not familiar with the basics. This post will show how to use this approach in Alteryx Designer. …


Find the patterns of customer or user behavior within your data. Market basket analysis can provide those new insights.

Image for post
Image for post
Photo by Madalin Tudose on Unsplash

I cook green bean casserole just once a year. Although it’s kind of a culinary travesty, we still make it with Thanksgiving dinner for sentimental reasons. Its essential ingredients are green beans, canned cream of mushroom soup and — most important — so-called “french fried” onions (also from a can) sprinkled on top. All three ingredients often are grouped together in the grocery store around the holidays.

Image for post
Image for post
Image from GIPHY

But how’d the grocery stores know to showcase those items together? Do they have a sentimental attachment to green bean casserole, too?

Nope, the stores are making the most of their customer data — and so can you. An analytic approach called market basket analysis reveals which items buyers purchase together. Among other purposes, this analysis can show retailers how to locate products together and how to cross-promote and recommend items that customers often put in their shopping carts at the same time. Marketing messages and promotions can highlight those items occurring together often, and key products that often relate to additional purchases can be identified. This approach works whether the stores and carts are physical or digital. Market basket analysis can also be used to analyze web browsing history, detect fraud and manage inventory. …


Interactive maps and predictive modeling for creepy phenomena…why not? Let’s have some Halloween fun with data science.

Image for post
Image for post
Photo by Gary Meulemans on Unsplash.

Whether you’re the kind of person who seeks out the spooky or not, guess what: You probably live near some creepy things.

To commemorate the season, we thought it would be fun to do some macabre mapping and petrifying prediction of spooky phenomena. Data science doesn’t have to be just for serious subjects! I’ll show you how I used Alteryx Designer, Python and the mapping package Folium to analyze and map these data.

The Spookiest Places in the U.S. (and the Least Spooky)

To look at how spooky U.S. metro areas are, I created a (silly) Spooky Score for each area, based on the density of cemeteries and haunted places in each metro area, as well as the per capita UFO sightings and Bigfoot encounters. …


Contribute your expertise to a good cause through one of these opportunities.

Image for post
Image for post
Photo by Tim Mossholder on Unsplash

Ready to put your data science skills to work — to help others?

No matter what career level you’re at, you too can participate in “data for good” events and activities. Whether you’re established in or aspiring to a data career, there are plenty of opportunities for you to contribute. You’ll get experience in new domains, new portfolio projects, and new connections with other data enthusiasts, plus you’ll feel great about contributing to a good cause!

Image for post
Image for post

While there are many general tech-related causes out there that you can join, we’ll look here at those that are primarily data oriented.

Organized Projects

Join a short- or long-term analytics or data science project or collaboration run by an established organization to advance a good…


Each student’s journey through a higher education institution creates lots of data. Use it to build models that support institutional and student success.

Image for post
Image for post
Photo by MD Duran on Unsplash

Caps, gowns, diplomas … and data!

Each student’s journey through a higher education institution creates lots of data. Recruitment, advising, retention, financial aid, administrative processes, assessment measures, course work, athletics and alumni activities all can be tracked in detail.

That data can be put to work in predictive models that advance institutional goals and aid student success. In addition to the effective use cases linked above, here are two more innovative ways researchers have used machine learning to make predictions in the world of higher ed. …


Automated processes free up human time and creativity. Maybe they’ll also make us better people.

Image for post
Image for post
Photo by Clem Onojeghuo on Unsplash

A research paper I read recently led me to consider: Could process automation not just empower humans by helping us avoid dull tasks, but also by fundamentally changing the way we think? Considering automated processes as collaborators with humans, not merely as simple replacements, opens up a whole new realm of possibilities for both humans and algorithms.

Around the same time, Alteryx hosted its first Twitter chat, addressing topics like the democratization of data and upskilling for the data professions. …


Top data professionals offer advice for interns on how to maximize their opportunities

Image for post
Image for post
Photo by Marvin Meyer on Unsplash

With internship season well underway, we reached out to some Alteryx ACEs, top analytics experts and participants in the Alteryx Community, to see what advice they’d offer to interns in data analytics and data science.

How can you make the most of an internship experience? What are key things to learn from the people and resources available during this unique opportunity? These data pros provide their perspective on how to be successful in an internship and beyond.

Jason Mack (@dataMack), Head of Analytics at Cigna

Image for post
Image for post

As an intern, your primary focus should be on building a network of connections that can help you land your next full-time role, or help at some point in the future. A great way to have people remember you is to solve some problem for them, even if it may seem simple or small. For example, an Alteryx workflow that helps them consolidate their weekly spreadsheets: if it saves them from the most boring and dreaded 20 minutes of their week, you have improved their life, and they will remember you. …


Data science has presented new possibilities for greater independence, improved care, and better outcomes for people with disabilities. Here are some examples of this kind of innovation.

Image for post
Image for post
Photo from Disabled and Here

Could the time it takes for you to water your houseplants say something about your health? Or might the amount you’re moving around your neighborhood reflect your mental health status?

When translated into data and analyzed, these measures could indeed provide insights into the health of people living with chronic physical or mental illness or disabilities.

Data science has presented new possibilities for greater independence, improved care and better outcomes. Whether it’s healthcare organizations using data to deliver care more effectively, developers creating data-driven apps that help identify early warning signs of illness, or inventors creating new sensors and devices to detect health issues, all these tools rely on data science techniques to help people living with disabilities or mental illness. …


What’s the magical combination of skills for data science? Let’s use data science to find out.

Image for post
Image for post
Photo by Marius Masalar on Unsplash

As data science enthusiasts know, there’s a lot more to excelling in the field than just its technical aspects. Data professionals need a wide range of skills, extending well beyond the technical aspects of data manipulation and analysis.

This week’s episode of the Alter Everything podcast showcases Carlene Jones, data and analytics consultant, and Nynne Haagensen, a data enthusiast who worked with Carlene. Their conversation reinforces that people skills, communication abilities and business savvy are all critical to success in data science and analytics.

What are all those skills? To explore online conversations around this skill set, I decided to gather and analyze some data, naturally, inspired by this fantastic topic modeling trilogy (part 3 is coming soon!). This seemed like a fun opportunity to apply topic modeling with Alteryx Designer to what folks have discussed out there on the interwebz about the data science skill set. (Topic Modeling is part of the Alteryx Intelligence Suite, which includes some new text mining tools.) …


Don’t just hit “Apply” on every data-related job ad. Maximize your odds with this advice from an experienced job search coach.

Image for post
Image for post
Photo by Tim Mossholder on Unsplash

Though data analytics and data science are still fields in demand right now, even those working in data-focused jobs have been affected by the recent economic upheaval. You might be seeking new possibilities or preparing to move into a new data role.

As you explore your opportunities, a little good advice can go a long way. We sought out some advice from a professional job search coach, so we reached out to Ashley Watkins, a Nationally Certified Résumé Writer. …

About

Susan Currie Sivek, Ph.D.

Data Science Journalist for @Alteryx . Data geek and former journalism professor and researcher. Writer, knitter, hiker, cyclist. Opinions mine. she / her

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store