A supergroup is a musical group whose members are already successful as solo artists – but even better together. Think legendary acts like the Traveling Wilburys, Journey, and Cream.
The concept of a supergroup sounds a lot like Alteryx and its technology partners. Each platform is an incredible performer on its own, but when you combine them together, you get even more star power – like faster insights and scalable processes.
But the trick with any music act is finding band members that can collaborate, and the same goes for your data ecosystem. Alteryx performs well with leading cloud and data platforms, and one of those superstars is Tableau.
Tableau is like the Stevie Nicks or the Mick Jagger of the data stack: it has a powerful stage presence. With beautiful visualizations and reporting capabilities, Tableau is all about presentation, making it the perfect lead singer for your data insights.
In this blog, we’ll explore a few winning supergroups with Tableau that will amplify your data insights. First, let’s talk about why Tableau and Alteryx play so well together, and the different data stacks you can use.
Alteryx + Tableau
You can’t have powerful data visualizations without powerful insights. It would be like having Hall without Oates. Tableau and Alteryx give you both.
Alteryx enables analysts and data scientists to spend less time discovering, preparing, blending, and analyzing data for Tableau, and more time visualizing and sharing insights. By creating rich, clean datasets and uncovering insights in Alteryx, you can then create richer reports in Tableau.
The process will often look like this:
- Join and clean data from disparate sources in Alteryx
- Run descriptive, diagnostic, predictive or even spatial analytics as needed (e.g., if you are building a map in Tableau)
- Reshape the data so it’s easily consumable for visualization in Tableau, and quickly convert to Tableau formats (.tde or .hyper)
- Pop out the report in Tableau and share with your organization
- Further manipulate data in Alteryx as you discover more questions to explore
Lapp Group uses Alteryx to analyze several thousands of transactions and data variables from its own systems as well as those of its distributors, third parties, and end-customers. Then, using Tableau for data visualization, Lapp can show its sales team the exact sources of customer demand, both by geography and by industry.
And if you want to make your supergroup even better? Alteryx also makes it easy to add more band members – like Snowflake.
Snowflake + Alteryx + Tableau (“SALT”)
I have a legendary supergroup acronym for you, and it’s not ABBA. It’s SALT: the combination of Snowflake, Alteryx and Tableau that customers like MillerKnoll love.
The SALT stack brings together every data player you need in a band (an end-to-end analytics architecture).
You have Snowflake for access to data, Alteryx for analytics, data science and machine learning, and Tableau for reporting insights. MillerKnoll used the SALT stack to establish an end-to-end process that empowers its sales team to better understand client needs.
You can make your SALT stack even more efficient using Alteryx Designer’s in-database capabilities with Snowflake to transform data before visualizing it in Tableau.
AWS + Alteryx + Tableau
Like an arena rock star, AWS knows how to put on a large-scale performance. When you combine AWS services with Alteryx and Tableau, you empower more employees to get the most out of cloud and take full advantage of data – especially if you feel like your org has enough data to fill a stadium.
For instance, to build its customer loyalty app, Chick-fil-A used Alteryx to manipulate billions of customer records in Amazon Redshift to filter out the pertinent data needed for Tableau functions, applying knowledge from line-of-business owners who wouldn’t normally have participated in the data transformation process. And Nielsen uses AWS, Alteryx and Tableau together to automate reports that serve thousands of end users across the organization.
Alteryx Auto Insights + Tableau
Alteryx Auto Insights and Tableau complement each other perfectly. Tableau visualizes data, while Auto Insights acts as an advisor on the data. Both have similar roles but different contributions – like having two guitar players, but one bass and one electric.
Dashboards and reports are a great tool for monitoring business insights, but analysts still need to do data discovery to identify root causes and ask new questions. Auto Insights does this discovery for the user, leveraging machine learning to uncover trends and opportunities.
In other words, Tableau excels at telling you what’s happening, and Auto Insights answers questions like, “What caused that change?” and “Why did it change?” By combining the two, you get both the what and the why.
Putting together a data supergroup is worth its weight in gold records. With thousands of hours saved and more valuable business insights, your business will put on a legendary performance.