Tableau and Alteryx are two well respected business intelligence (BI) and data analytics platforms. Such applications are seeing growing demand, as business are increasingly focused on data mining their vast troves of data – both cloud and on-premise.
Whether from relational databases, enterprise applications, unstructured data, social media, or other sources, there is more data than ever that is subject to analysis. Furthermore, data mining techniques are becoming ever more sophisticated, increasing the demands on platforms such as Tableau and Alteryx.
As two popular data analytics platforms, users often are forced to choose between Alteryx and Tableau. There are arguments for and against each. It is hard to say that you could go wrong with either data tool. But which is best for your organization’s data analytics needs?
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Tableau vs. Alteryx: Key Features Comparison
Tableau is very much focused on delivering analytics with artificial intelligence, data management, and collaboration. At the heart of Tableau is a proprietary technology called VizQL that makes interactive data visualization an integral part of understanding data. It differs sharply from traditional tools that require the user to analyze data in rows and columns, choose a subset of the data, and then create a chart from that data. In contrast, VizQL skips those steps and creates a visual representation right away, providing visual feedback as you analyze.
Tableau certainly excels at visualization, which has not been a strength of Alteryx. Instead, Alteryx’s strong point has been in cleansing data, so it has been more useful for analysts in ensuring data and visualization accuracy. Why visualize or analyze inaccurate data?
Alteryx is designed to extract, transform, and load (ETL) data from a great many data sources. It engages with data via workflows throughout the ETL process. Repeatability of processes saves a lot of time on manual processes and data reentry. Alteryx does well on data discovery and management tools, too. But reporting is limited. The platform does generate reports, but these are only for direct Alteryx BI users. Yet Analytic Templates help in loading data into third-party visualization platforms.
Latest Features and Updates
Tableau, of late, has been adding features like Ask Data in Slack (ask questions using natural language and automatically get data visualizations), Einstein Discovery in Slack (predictions in work flow), and Model Builder (collaboratively build and consume predictive models using Einstein).
Alteryx, meanwhile, just boosted its platform with the release of Alteryx Analytics Cloud, which extends its analytics capabilities to a much wider set of users across the enterprise. Users now only need a browser to gain access. An automated modeling solution has been added, too, which doesn’t require data science experts to code machine learning models. Further new features include the ability to find anomalies and insights hidden in data, and provide summaries and explanations focused.
Tableau wins in terms of depth of analysis and the kind of features that data scientists, analysts and power users look for. But Alteryx closed the gap with the cloud analytics features it recently unveiled.
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Is Tableau or Alteryx Easier to Use?
Newer users are likely to find Alteryx easier to use than Tableau. Some complain that Tableau has a steep learning curve; users should be well-versed in working with the R programming language, which is used heavily in statistical programming and data analysis.
But Tableau has been working to become easier to use. Its AI-powered analytics features lower the barrier to data science techniques. Tableau works really well when Excel and statistical data are used as sources. For other formats, ease of use can suffer.
Alteryx has never had a reputation for being difficult to use. But its new cloud version makes it even more accessible. Anyone with a browser can access the platform and setup can now be done in minutes. Its low-code/no-code capabilities also make it easier for any user to extract insights that help them tackle their toughest business problems.
The conclusion: Alteryx wins on broad usage by a non-technical audience, whereas Tableau wins with more technical and advanced users.
Tableau vs. Alteryx: Analytics Comparison
Tableau tries to differentiate itself with what it describes as an intuitive analytics experience, with richer capabilities based on its VizQL engine. It can connect to data live (performing queries in-database and returning results in real-time) or in-memory (ingesting data from source systems into Tableau). This allows users to control performance, cost, and data freshness. Tableau also scores very well on live query capabilities and extracts, helping analysts to query faster. Its use of the R language makes it the winner on statistical capabilities.
Alteryx was way behind on analytics capabilities until recently. Its newly released cloud version extends analytics beyond data scientists, IT, and data analytics departments to lines of business groups. Any user can use its Designer Cloud to prepare, blend, and output data in a visual, code-free way through a browser, including on Macs.
Tableau wins on analytics capabilities, but if Alteryx’s recently unveiled analytics capabilities live up to the promised functionality in company press releases, they will have closed the gap considerably. And due to ease of use, many users may find Alteryx a better option.
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Tableau vs. Alteryx: Cloud and On-Premise
Both Tableau and Alteryx evolved from the on-premises world. And both platforms have been working to change that.
Tableau offers cloud-hosted solutions such as Tableau Online and Tableau CRM, but its strength lies in on-premises deployments and this is where much of its massive installed base resides. Thus, it can be challenging to scale out Tableau workloads in the cloud.
Alteryx just came out with its cloud-based platform, which probably puts it ahead for now. Its Designer Cloud is interoperable with Alteryx’s Designer Desktop product and users can easily collaborate and share workflows between both applications.
Tableau vs. Alteryx: CRM Comparison
CRM and BI often go together. With Tableau now owned by Salesforce, it has excellent marketing and enterprise product capabilities and is being integrated with Salesforce Einstein Analytics (known as Tableau CRM). An Einstein Discovery dashboard extension, for example, brings predictive modeling capabilities from Einstein to Tableau.
Alteryx doesn’t attempt to offer CRM, although its ETL and analytics capabilities can comfortably deal with data imported from CRM systems. But it stops short of CRM functionality. Thus, for those wanting integrated CRM, Tableau wins.
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Tableau vs. Alteryx: Comparing Integration
Tableau has its hands full in integrating with Salesforce. This creates a somewhat fragmented experience between Einstein Analytics and Tableau, but steady progress is being made in bringing both together. It likely won’t be long until those issues are resolved. As a result, Salesforce customers will be upsold to Tableau and vice versa.
Alteryx provides dozens of data connectors that make it easy to import and make edits to incoming data. Users can integrate Alteryx with other cloud applications, databases, and spreadsheets. Cloud storage connectors are available for platforms like Amazon S3, Google Drive, Office 365, and Snowflake.
Alteryx, then, is largely free of integration headaches. Its cloud-based approach simplifies its deployment and use. Alteryx wins here.
What is the Price Difference Between Tableau and Alteryx?
Tableau has a reputation for being expensive. By some estimates, it works out to about $75 monthly per user for decent analytics functionality. But those who only want to interact with some basic dashboards can get it much cheaper. That said, the addition of Tableau CRM for a list price of up to $150 monthly per user means newer functionality and Salesforce integration don’t come cheap.
Alteryx has a completely different pricing model, so it is hard to compare them. It offers annual subscriptions. Alteryx Designer costs $5,195 per year. Additional capabilities come for a hefty fee. It looks like Tableau comes out ahead for some bids, but not all. This one depends on the needs of each organization.
Tableau vs. Alteryx: Conclusion
Tableau boasts a large and enthusiastic user base and a very loyal user community. Its profile in the marketplace is high. Tableau’s popularity is growing, too, partially through the distribution of a free platform known as Tableau Public. This is where people can share and explore data visualizations online. It contains over 3 million interactive visualizations. Yet it is in the data scientist, analytics specialist, and power user markets where its feature set wins the most plaudits. In these markets, it is likely to be favored over Alteryx.
Alteryx has a reputation for being easier to use. While it used to be more of an ETL and data cleansing platform, it has expanded its analytical capabilities to rival Tableau. Its new cloud platform will no doubt win it orders from Tableau. For those that want decent analytics capabilities without requiring heavy duty capabilities, Alteryx probably wins.
Note though, that Gartner did not include Alteryx in its latest “Magic Quadrant (MQ) for Analytics and Business Intelligence Platforms.” Tableau was graded Tableau as a leader. Gartner will wait to see what users say in its surveys to see if Alteryx’s new cloud capabilities merit entry into the MQ.
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