Alteryx has been generating some buzz. Recently named a Visionary by Gartner in two separate Magic Quadrants (Advanced Analytics Platforms and Business Intelligence and Analytics Platforms), Alteryx also closed a $60MM Series B round of financing, bringing their total warchest up to $78MM. Venture funding came from a mix of big name VCs including Insight Ventures, SAP Ventures (now Sapphire), Thomson Reuters and Toba Capital.
I joined Seann Gardiner, VP of Business Development at Alteryx for a tour of the product, and a discussion about what separates Alteryx from the growing field of competitors.
As a more mature offering (company was founded in 2010), Alteryx is feature rich, and has been built to enable business/data analysts to on-board raw data and spit out analysis. Data blending, data augmentation, advanced analysis (i.e. spatial and predictive with R), and reporting/exports are all provided for in Alteryx, setting it up against cradle-to-grave peers like ClearStory. Seann summed up Alteryx in a nutshell:
“Alteryx is to SAS/SPSS what Tableau is to Business Objects/Cognos”
What really sets Alteryx apart from its peers is the “Alteryx Analytics Gallery”, an app store for pre-built analytic applications. Public apps provided by Alteryx and 3rd party contributors enable quick solutions to common problems, and the platform also supports the ability for companies to leverage a similar gallery in-house and share analytic apps among specified team members.
Workflow components included in the offering are:
1. Data Blending
Alteryx offers a range of supported data formats, from the standard flat files and RDBMS connections, to Big Data connectors (MongoDB, Hadoop, Greenplum), enterprise databases (SAP, DB2, Teradata), social data feeds (GNIP, DataSift, FourSquare), geodata (OpenGIS, GeoJSON) and more. The breadth of named connectors is extensive, and there also exists generic connectors for munging in more esoteric data sources.
2. Data Augmentation
The official augmentation sources list 5 partners specific to data augmentation (DigitalGlobe, D&B, Experian, TomTom and U.S. Census), but lines between what is a data blending source and what is a data augmentation source are not as clear cut in Alteryx. There exists connectors for data sources that can be used for augmentation, and the multi-purpose web connector which allows connections to web service APIs.
Alteryx is aimed at the savvier analyst. The tool incorporates R for its statistical and analytical engine, with complex functions able to be snapped in place as part of the visual workflow designer. Even with the drag and drop simplicity for integrating complex analytics, the user still needs to know when to use a linear regression or binary logistic regression, and how to properly configure each.
Once an analysis has been completed, the output can be uploaded to the cloud using the Alteryx Analytics Gallery, or piped to BI tools like Tableau and Qlik.
As for success in the market, Alteryx reports a customer base of over 600+ companies, 200,000+ users and a 95%+ contract renewal rate. It’s worth noting that the company has seen such rapid growth, the client count reported across press releases, powerpoint decks and corporate website are all out of sync. A great sign in a growing company.
All told, the Alteryx offering is an aggressive one.