A platform for analytics, data science, and process automation
our rating 4.5 out of 5 Stars

AlteryxProduct Overview

  1. About Alteryx
  2. Pros of Alteryx
  3. Cons of Alteryx
  4. Breakdown of core features

Alteryx product overview

Alteryx is a solution designed to be a launchpad for automation breakthroughs that can be used for personal growth, achieving transformative digital outcomes, or rapid innovation. It is a unique innovation that converges analytics, data science, and process automation into one platform. Alteryx empowers everyone and every organization to make business-altering breakthroughs the new status quo.

Alteryx has the Designer feature to automate every analytics step — from data prep to data science. It lets users access any data source or data type, then experience smart data preparation and blending via a simple drag-and-drop interface. Users can blend data from spreadsheets, documents, cloud sources, databases, EDW, data lakes, enterprise applications, and RPA bots.

Alteryx provides an automated optical character recognition and natural language processing to accelerate text analytics and text mining. It allows users to visualize and explore data with instantly generated data profiles and spot patterns to speed discovery and insights. Users can enrich these insights with third-party packages for data mapping and geocoding. These packages include geospatial, demographic, and firmographic information.

This solution offers code-first and low-code processes. Users can leverage integrated R and Python tools. Alteryx also has no-code options available to put the power of analytics in the hands of everyday users.

Alteryx automates repetitive processes to drive faster actions. Users can connect Alteryx automated workflows with process intelligence systems or RPA bots. It enables users to publish insights to interactive dashboards, or send them directly to numerous enterprise applications and RPA systems. These include Microsoft Office, Microsoft Power BI, XML, Adobe PDFs, cloud data services, databases, and RPA bots. Users can also publish to web apps via native integration into Tableau, Qlik, ThoughtSpot, UiPath RPA, SAP, Salesforce, Microsoft Azure, Google, and Adobe.

Pros of Alteryx

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  • Lets users connect to data from anywhere and deploy models with AutoML.
  • Enables users to build once and automate permanently with workflows and analytic apps.
  • Eliminates the need for multiple tools through automated data processes.

Cons of Alteryx

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  • Alteryx requires desktop download and is not mobile-friendly.

Breakdown of core features

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Alteryx includes technologies for analytics, data science, and process automation.

Data collaboration

Alteryx lets users share analytic apps, and collaborate with teams and decision makers. They can also create and share data insights, via apps and reports.

Data science and analytics

Alteryx lets users prep, blend, and analyze data via repeatable workflows. They can connect, access, and blend business data from anywhere, and build data models with low-code, no-code, and expert options.

Visual analytics and modeling

With Alteryx, users can see each step of the analytics process in a visual interface. Teams can use interactive visualizations to validate their model results, then output spatial analytics to easy-to-interpret mappings and visualizations for better outcomes.

(Last updated on 02/02/2022 by Liz Laurente-Ticong)

Quick Facts

  • Industry Specialties
    All Industries
  • Pricing
  • Works Best For
    Any Sized Businesses





  • Data Analysis
  • Data Cleansing
  • Data Connectors
  • Data Enrichment and Insights
  • Data Joining
  • Data Mining
  • Data Profiling
  • Data Science and Decisions
  • Data Source Connectors
  • Data Source Integrations
  • ETL Capability
  • In-memory Data Model
  • Machine Learning
  • ML Algorithm Library
  • Mobile Reporting
  • No-Code Sandbox
  • Publish to PDF
  • Self Service Analytics
  • Self Service Data Preparation
  • Visual Workflow Management


  • Adobe Analytics
  • Amazon Athena
  • Amazon Aurora
  • Amazon Redshift
  • Amazon S3
  • Apache Cassandra
  • Apache Hive
  • Apache Spark
  • AWS
  • BigQuery
  • Databricks
  • dBASE
  • Exasol
  • Google Analytics
  • Google BigQuery
  • Google Maps
  • Google Sheets
  • Hadoop
  • HortonWorks
  • IBM
  • IBM Db2
  • MapInfo Pro
  • Marketo
  • Microsoft Access
  • Microsoft Azure
  • Microsoft BI (MSBI)
  • Microsoft Cognitive Toolkit
  • Microsoft Dynamics 365
  • Microsoft Excel
  • Microsoft Office
  • Microsoft OneDrive
  • Microsoft Power BI
  • Microsoft SharePoint
  • MongoDB
  • MySQL
  • NetSuite
  • Oracle
  • PostgreSQL
  • QlikView
  • Salesforce
  • SAP
  • SAS
  • Snowflake
  • Splunk Cloud
  • SPSS
  • SQL Server
  • SQLite
  • Tableau
  • Teradata Vantage
  • Vertica

Pricing Model

  • Quote-based


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