Alteryx and H2O.ai compete in the data science and analytics space. Alteryx generally has the upper hand due to its user-friendly workflow and superior support, while H2O.ai offers advanced machine learning features appealing to skilled analysts.
Features: Alteryx provides an intuitive drag-and-drop interface for data preparation, blending, and analytics, making it easy to use without coding. It excels with tools for spatial and geographic analysis, enabling complex workflows for data enrichment. H2O.ai offers a rich suite of machine learning algorithms and automated AI capabilities, promoting efficiency in building and deploying AI models. H2O.ai's predictive analytics features add value beyond the manual tools in Alteryx.
Room for Improvement: Alteryx could enhance its machine learning capabilities and scalability to cater to more data science use cases. There is room for expanding cloud integration options and automation features to streamline operations further. H2O.ai might benefit from improving ease of use and simplifying its setup process for broader accessibility. Enhancing support and user guidance could also attract more users who are not as technologically adept.
Ease of Deployment and Customer Service: Alteryx offers straightforward deployment with seamless integrations and robust support, making it accessible to various users. Its extensive guidance ensures efficient use. H2O.ai provides flexibility with cloud solutions tailored for AI needs, though it might require more expertise for deployment. Despite this, its AI-driven insights support complex projects efficiently.
Pricing and ROI: Alteryx involves higher initial costs, justified by valuable data processing returns and predictable licensing models. H2O.ai's modular pricing approach offers flexibility, making it appealing for companies focusing on specific AI functionalities. H2O.ai's pricing structure is advantageous in environments prioritizing advanced AI features, potentially leading to significant ROI through enhanced capabilities.
| Product | Market Share (%) |
|---|---|
| Alteryx | 5.7% |
| H2O.ai | 1.7% |
| Other | 92.6% |
| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 15 |
| Large Enterprise | 51 |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 3 |
| Large Enterprise | 7 |
Alteryx can be used to speed up or automate your business processes and enables geospatial and predictive solutions. Its platform helps organizations answer business questions quickly and efficiently, and can be used as a major building block in a digital transformation or automation initiative. With Alteryx, you can build processes in a more efficient, repeatable, and less error-prone way. Unlike other tools, Alteryx is easy to use without an IT background. The platform is very robust and can be used in virtually any industry or functional area.
With Alteryx You Can:
Alteryx Features Include:
Some of the most valuable Alteryx features include:
Scalability, stability, flexibility, fast performance, no-code analytics, data processing, business logic wrapping, scheduling, ease of use, data blending from different platforms, geo-referencing, good customization capabilities, drag and drop functionality, intuitive user interface, connectors, machine learning, macros, simple GUI, integration with Python, good data transformation, good documentation, multiple database merging, and easy deployment.
Alteryx Can Be Used For:
Alteryx Benefits
Some of the benefits of using Alteryx include
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Reviews from Real Users
"Automation is the most valuable aspect for us. The ability to wrap business logic around the data is very helpful." - Theresa M., Senior Capacity Planner at a financial services firm
"Alteryx has made us more agile and increased the speed and effectiveness of decision making." - Richard F., Director, Digital Experience & Media at Qdoba Restaurant Corporation
"The scheduling feature for the automation is excellent." - Data Analytics Engineer at a tech services company
"The product is very stable and super fast, five-star. It's significantly more stable than its nearest competitor." - Director at a non-tech company
“A complete solution with very good user experience and a nice user interface.” - Solutions Consultant at a tech services company
"There are a lot of good customization capabilities." - Advance Analytics PO at a pharma/biotech company
H2O is a fully open source, distributed in-memory machine learning platform with linear scalability. H2O’s supports the most widely used statistical & machine learning algorithms including gradient boosted machines, generalized linear models, deep learning and more. H2O also has an industry leading AutoML functionality that automatically runs through all the algorithms and their hyperparameters to produce a leaderboard of the best models. The H2O platform is used by over 14,000 organizations globally and is extremely popular in both the R & Python communities.
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