KNIME.COM

KNIME Analytics Platform

5 / 5 1 review


Average Ratings

1 Review
  • 5 / 5
    Overall
  • 4 / 5
    Ease of Use
  • 5 / 5
    Customer Service

Product Details

  • Starting Price
    Not provided by vendor
  • Deployment
    Installed - Mac
    Installed - Windows
  • Training
    In Person
  • Support
    Online

Vendor Details

  • KNIME.COM
  • www.knime.org
  • Switzerland

About KNIME Analytics Platform

Math & statistical functions, workflow control, advanced predictive & machine learning algorithms, and more for data scientists.


62712

KNIME Analytics Platform Features

  • AI / Machine Learning
  • Benchmarking
  • Data Blending
  • Data Mining
  • Demand Forecasting
  • For Education
  • For Healthcare
  • Modeling & Simulation
  • Sentiment Analysis

KNIME Analytics Platform Reviews Recently Reviewed!


KNIME is a powerhouse for all types of analysis, including machine learning.

Mar 01, 2018
5/5
Overall
4 / 5
Ease of Use
4 / 5
Features & Functionality
5 / 5
Customer Support
5 / 5
Value for Money
Likelihood to Recommend: 10.0/10 Not
Likely
Extremely
Likely

Pros: KNIME desktop is a powerful tool for building analytical workflows. The visual interface is extremely helpful. They also have extensions to integrate other tools like R and Python into the workflows. Best of all you can share your workflows with others - great for reproducible research. There are built in tools for many types of supervised and unsupervised machine learning. The desktop application is free and open source. The support community on the KNIME website is very active and responsive. To extend the features you can purchase KNIME server.

Cons: Like any new tool there is a learning curve. However, they have lots of videos, examples and an active support community. There are some features that are not intuitive, such as how to use flow variables. In general I have found that I use R much less now and do most of my analysis in KNIME. KNIME is primary drag and drop and requires little to no coding.

Overall: We were able to build a reproducible workflow for analyzing our data and creating actionable insights.