Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms.
| Product | Market Share (%) |
|---|---|
| KNIME Business Hub | 12.3% |
| Alteryx | 5.9% |
| Domino Data Science Platform | 2.7% |
| Other | 79.1% |
| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 15 |
| Large Enterprise | 51 |
| Company Size | Count |
|---|---|
| Small Business | 20 |
| Midsize Enterprise | 16 |
| Large Enterprise | 29 |
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
:
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
Domino provides a central system of record that keeps track of all data science activity across an organization. Domino helps data scientists seamlessly orchestrate AWS hardware and software toolkits, increase flexibility and innovation, and maintain required IT controls and standards. Organizations can automatically keep track of all data, tools, experiments, results, discussion, and models, as well as dramatically scale data science investments and impact decision-making across divisions. The platform helps organizations work faster, deploy results sooner, scale rapidly, and reduce regulatory and operational risk.
KNIME Business Hub offers a no-code interface for data preparation and integration, making analytics and machine learning accessible. Its extensive node library allows seamless workflow execution across various data tasks.
KNIME Business Hub stands out for its user-friendly, no-code platform, promoting efficient data preparation and integration, even with Python and R. Its node library covers extensive data processes from ETL to machine learning. Community support aids users, enhancing productivity with minimal coding. However, its visualization, documentation, and interface require refinement. Larger data tasks face performance hurdles, demanding enhanced cloud connectivity and library expansions for deep learning efficiencies.
What are the most important features of KNIME Business Hub?KNIME Business Hub finds application in data transformation, cleansing, and multi-source integration for analytics and reporting. Companies utilize it for predictive modeling, clustering, classification, machine learning, and automating workflows. Its coding-free approach suits educational and professional settings, assisting industries in data wrangling, ETLs, and prototyping decision models.
