Tableau Prep, Alteryx, and Power Query are all visual, low-code canvases to clean and reshape data, but each one is anchored differently. Prep feeds into Tableau, Power Query feeds into Excel and Power BI. But, Alteryx doesn't care what the output is used for afterward. In fact, with Alteryx, you're able to output the finished data as a .hyper file, which is used in Tableau. Here's what all three handle well, each of their strengths, and where Alteryx differs from both.
What They All Share
For everyday data cleaning, the tools cover similar areas:
- Visual, little to no code workflow
- Connect to common data sources like Excel, CSV and databases
- Join/merge, union/append, or blend datasets
- Clean data: rename fields, fix data types, remove duplicates, filter, aggregate
- Reshape data: pivoting, transposing data, splitting columns
- Previews of results at every step
- Save a workflow and can rerun as data refreshes
If your data prep mainly needs these options, all of them will get you there. There are differences that show up past these basic data preparation steps, though.
Bundled Tools
Tableau Prep and Power Query share the same appeal (they're already paid for). Prep comes bundled with a Tableau Creator license, so it makes it easy to incorporate if a team already has Tableau. On the other hand, Power Query is built directly into Excel and Power BI desktop and it's completely free with Microsoft.
Both of these also have simpler, click-driven interfaces. While Power Query does have a coding language called DAX (Data Analysis Expressions) for people more familiar with coding, most data cleaning can get done without using complex DAX formulas. Adding on, Power Query records every transformation in plain language as a steps you can edit or reorder. Prep shows inline bar charts, previews, and distributions as you shape the data. That makes the learning curve much smaller for these tools than Alteryx's more formula driven canvas. For many teams, Prep or Power Query will be the right amount of tool for the job.
Alteryx's Strengths
Once there are needs for more than just data cleaning and reshaping, Alteryx has options that neither Power Query or Prep covers:
- Predictive & statistical analytics: built-in regression, time series forecasting, clustering or optimization with no coding needed. Prep and Power Query don't offer this natively.
- Spatial analysis: drive-time, trade-area, or spatial matching tools that have results exportable to spatial file formats. Again, don't exist in Prep or Power Query.
- Data Source Connectors: a lot of native connector sources and the ability to blend different file structures into the same flow.
- Enterprise Automation: Alteryx Server runs unattended workflows at scale. Power Query needs Power BI Dataflows or Azure Data Factory as well to compare, and Prep's built in scheduler is useful, but definitely limited in comparison.
With all this, it does come at a cost. Alteryx could cost up to $5,000 per user per year, against the basically free Power Query, and a few hundred dollars a month Tableau Prep.
When to Use Tableau Prep
- Recurring cleanup to feed into a Tableau dashboard: Weekly or monthly reports, potentially in csv format, that needs renaming, type fixes, joins or unions before it gets sent to a workbook
- Teams already on a Tableau Creator license: If Prep is already paid for, then it just makes sense to use this along with Tableau!
- Non-technical business users needing self-serve prep: The click and preview interface is very approachable for people unfamiliar with formulas or more technical analytical tools
When to Use Power Query
- Reporting Excel workbooks: Power Query already lives inside Excel, so combining worksheets and csvs into one workbook and refreshing it with one click is super useful, without having to export to another tool
- Prepping data inside Power BI Desktop: If you're already using Power BI, it's much simpler to use the built-in Power Query tool instead of importing/exporting
When to Use Alteryx
- Forecasting or predictive modeling: Forecasting demand, or a subscription business predicting churn, would need that model built in their data prep workflow
- Location-based decisions: If a business is evaluating store locations, doing drive-time and trade-area analytics directly on the data is simple, no extra tool needed
- Enterprise-scale along with automation: Combining ERP, CRM, API data from multiple departments into one data pipeline, then being able to run it unattended on a schedule with permissions and an paper trail. This is a prominent strength of Alteryx
Final Thoughts
None of these tools are really competing for the same use cases. Prep and Power Query are fast, low-cost, user-friendly and tied to their respective BI tools that many people already use. Alteryx stands by itself as an analytics platform where prep is just the first step. A lot of teams end up using a combination of these tools. They could have a tool for daily cleanup, then Alteryx for heavy data analytics. It's important to pick the right one based on how complex the data actually is, not just based on which one sounds the most powerful.