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By Curtis Burkhalter and Kate Butcher (@KateButcher)
We are thrilled to introduce Alteryx Copilot for Alteryx Designer Desktop. Alteryx Copilot harnesses the power of Generative AI to streamline your workflow creation and empower your analytics journey, allowing you to ask questions about your Alteryx workflows or data and receive answers in seconds. Whether you're an experienced data analyst or just getting started, Alteryx Copilot is designed to help you get more out of your data, faster than ever before.
Data professionals often face challenges when working with any analytics platform, whether that be manually selecting the right tool configurations or finding efficient ways to generate insights. Alteryx Copilot addresses these issues by allowing you to interact with your data in a natural, conversational manner. Simply tell Alteryx Copilot what you're trying to accomplish, and it will suggest the appropriate tools and even place them directly onto the canvas for you. This AI-powered assistance reduces the time spent on setup and allows you to focus on what really matters—analyzing your data.
Unlike some other Generative AI-powered products in the market, Alteryx Copilot can do all of this without using any actual data points; rather, it uses context such as data and workflow metadata like column or file names. This is huge because it ensures customer data is not transmitted to the LLM powering Alteryx Copilot. With Alteryx Copilot you can be confident that Alteryx is serious about data governance when it comes to AI.
Alteryx Copilot is tailored to meet the needs of users across your organization:
- For the Data Analyst: Copilot eliminates the tedious process of manually configuring tools or finding the right tool for the job, providing you with quick recommendations and automating tool placement. This helps you build workflows with greater efficiency, enabling you to concentrate on generating insights.
- For the Business Professional: Copilot offers a simplified interface that allows non-technical users to engage with data analytics without needing extensive technical knowledge. This means you can easily generate meaningful insights and make data-driven decisions without getting bogged down by technical complexities.
- For the Data Leader: Copilot will allow you to upskill and accelerate the onboarding of new team members, achieve efficiencies across existing team members so that they can focus on high-value work, and allow you to make data-driven decisions faster.
How To Access Alteryx Copilot Today
Join the Alteryx Copilot Preview today! By accessing this link, you can say goodbye to tedious manual processes and welcome accelerated analytics insights. With Alteryx Copilot, you’re not just getting an analytics tool—you’re gaining a strategic advantage in workflow creation. With the power of Generative AI, Alteryx Copilot drastically reduces the time spent on manual configurations, freeing up your valuable resources for more meaningful tasks.
Alteryx Copilot in Action
To begin, let’s assume that I’m no longer a Product Manager here at Alteryx, but rather I own an import/export business that specializes in finding the best wines to sell to local restaurants.
As someone who prides myself on providing the best possible wines to my restaurant clients, it is part of my job to compare the wines across years and look for changes in wine properties, alerting me to possible changes in overall quality. One of the main wine qualities that I always look towards from a consistency standpoint is the alcohol content of their wines, so my end goal is to compare wines across years, looking for changes in alcohol content.
I will be working with two datasets that look at various properties of wine quality for about 600 wines across the years 2023 and 2024. You can see from the screenshot below that the data contains information such as the pH, density and alcohol content of various wines, along with a year and a unique vintner code for each wine.
The first thing I will do once I’ve loaded my two datasets is join them together so that I can begin to compare them across years. With a simple request to Copilot, the user receives the following:
- The Join tool is automatically added to the canvas
- The tool is pre-configured for the user, and
- A basic description of what Copilot has done is added to the chat window, educating the user on what and why certain actions are done.
Additionally, this ability to blend datasets automatically using Alteryx Copilot is a huge advantage over some of our competitors, such as Microsoft, which recently introduced its own M365 Copilot in Excel. Even with the M365 Copilot, Excel still is a single dataset tool and is unable to perform blending tasks such as this.
We can see from the previous request that all of the columns for the ‘wines_2024’ dataset were given the default name of ‘Right_column_name’ as is standard when joining datasets using Designer. What I’d like to do next is provide them with a slightly more descriptive name that tells me to which year those column names refer, so again, I will ask Copilot to help me here to rename the columns.
Copilot has added the correct tool, which, in this case, is the Select tool. The really interesting thing is that I never referenced the ‘Select’ tool in my prompt to Copilot. For the users of Alteryx Copilot, this means that:
- Alteryx Copilot uses your natural language meaning to infer Alteryx specific language
- This Alteryx-specific language is converted by Copilot into the correct tools to help me accomplish my tasks
One final example of how Copilot can be helpful is the ability to use natural language to inject customization into our dataset. Knowing that, I’ve asked Copilot to create a custom column based on existing alcohol quantity columns for 2023 and 2024.
We see that Copilot adds a Formula tool, creates a new column name, and even creates a custom formula for me, making it easy to determine which wines had a different alcohol content from one year to the next. The ability of Alteryx Copilot to understand my request means that:
- Users no longer have to memorize syntax to get the answers they want
- Users can learn advanced data manipulations they may not have thought of, without a deep technical understanding
- Human errors are minimized, improving reliability
Key Takeaways
With a few quick examples, we have learned:
- Alteryx Copilot allows users to make simple requests in natural language, which are then automatically converted into the specific language and tools needed for Alteryx. This makes it easier for users to initiate complex operations without specialized knowledge.
- When a request is made, Alteryx Copilot automatically adds and configures the appropriate tools on the Alteryx canvas. This automation speeds up workflows and reduces the need for manual setup, saving time and reducing errors.
- Alteryx Copilot provides basic explanations in the chat window about what actions it has taken and why. This educates users on Alteryx functionality, allowing them to learn advanced data manipulations in a straightforward manner.
- With Alteryx Copilot handling the tool configuration and syntax, users no longer need to memorize complex commands, which minimizes human errors and improves the reliability of data workflows. This contributes to a more efficient and error-free data processing experience.
These are just a few examples of what you can currently accomplish with Alteryx Copilot, and we are working every day to improve and add new capabilities. We invite you to be among the first to try out Alteryx Copilot by signing up for our exclusive Alteryx Copilot Preview waitlist here.
