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KNIME Server Large BYOL for AWS

KNIME | 4.12.2

Linux/Unix, Ubuntu 20.04 LTS - 64-bit Amazon Machine Image (AMI)

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External reviews

37 reviews
from G2

External reviews are not included in the AWS star rating for the product.


    John H.

Create actionable insights using KNIME Analytics

  • July 30, 2019
  • Review provided by G2

What do you like best?
KNIME Analytics is a powerful tool for building analytical workflows. It provides many options for text parsing, especially CoreNLP and OpenNLP. Also, KNIME Analytics allows integration with open source software, such as R, Phyton and Spark. The software is free but you may purchase a server license to have a process run automatically with large amounts of data from many sources. There are built in tools for many types of supervised and unsupervised machine learning.
What do you dislike?
KNIME Analytics is a very complex tool, so it has a steep learning curve. Another thing I don’t like about it is that it tends to use a lot of memory of your computer, which affects the general performance of the machine. KNIME Analytics is primary drag and drop and requires little to no coding.
What problems are you solving with the product? What benefits have you realized?
The use of this platform is for NLP related tasks. We were able to build a reproducible workflow for analyzing our data and creating actionable insights by just using KNIME Analytics. It was deployed in my company 2 years ago and it has proved to be a high-value predictive analytics tool, as well as an accurate way to find patterns as a data mining tool.
Recommendations to others considering the product:
The tool is very intuitive with a lot of examples to learn. I would recommend it for members of the IT department with some deep software knowledge. You and your team must master R/Phyton in order to implement this solution effectively.


    Elias F.

Press a single button and run multiple commands

  • July 30, 2019
  • Review provided by G2

What do you like best?
KNIME Analytics is very useful to analyze large data quantities with advanced algorithms. Also, you are able to code without programming because can use block modules that do a specific tasks. It comes with several extensions that make text processing an easy process, something that’s a headache in other similar platforms, and with extensions to integrate other tools, like R, into the workflows. Use and integrate with cloud and big data environments.
What do you dislike?
You actually need more help than provided by block description if you want to do complex data analysis work. The user of KNIME Analytics needs to have a deep knowledge about R/Phyton in order to get the best out of the statistical analysis. If you want to do advanced data analysis and classification, it's mandatory to have engineering knowledge. There are some features that are not intuitive, such as how to use flow variables.
What problems are you solving with the product? What benefits have you realized?
With KNIME Analytics Platform we have turned manual tasks in easy and fast ones by just pressing a button to run multiple commands. We mainly use it for creating multivariate analysis and finding statistical significance of variables.
Recommendations to others considering the product:
Recommended for coders with some deep knowledge of R/Python. Yes, you can get a free RapidMiner license to process up to 50,000 lines of data, but this is not enough for big projects. Also, Consider KNIME Analytics does not replace a regular reporting tool.


    Jonathan G.

Advanced data analysis and AI

  • July 18, 2019
  • Review provided by G2

What do you like best?
When we had to go through data sources with tons of data, transforming the raw data for analysis was always the hardest part. With KNIME, this process can be automated, while the data acquisition model can be saved and run repeatedly, which saves a lot of time. It also provides a wide range of options for integration, allowing multiple languages like Python, R or Java and supporting formats like JSON and XML. What I like is that I can process large quantities of data while data cleansing and blending of tables can still be done very easily.
What do you dislike?
KNIME Documentation is poor, so it’s hard to find serious ans straightforward information out there. If you have any doubt, you may find yourself struggling to find a solution. Also, some tools for script writing and development are not easy to use, so you have to run tests to see how they perform, or some of them don't have enough features.
What problems are you solving with the product? What benefits have you realized?
We have been using KNIME in the IT department for advanced data analysis and experiments in the machine learning field. Also, we have used it on client data analysis for running prediction models.
Recommendations to others considering the product:
KNIME Analytics Platform is a great software for data ingestion given various formats. I think it would a great fit for medium size or big companies which have to handle with complex data analysis. If you want to use for experimentation in the AI area, this will work very well too.


    Ken K.

Great open source multi platform application for analytics

  • July 17, 2019
  • Review provided by G2

What do you like best?
It's really great to have an easy to use GUI, compared to other open sourced applications that utilize the same data
What do you dislike?
Certain API functionality still needs to be improved, primarily image mining plugins
What problems are you solving with the product? What benefits have you realized?
We use this primarily for creating data flows, integrating with mysql for our infrastructure analytics.


    Consumer Electronics

Data Analytics tool anyone can use. No programming skills are required

  • July 01, 2019
  • Review provided by G2

What do you like best?
Ease of use, variety of nodes and functions, its integrity with Cloud platforms, possibility to implement Python, R, Java scripts. Its good that you can see the model visually, as doing ETL. That's a big plus compared to other tools and scripting.
What do you dislike?
Its already slow as cost of friendly UI and becomes even slower as you install extensions. Not to mention opening the software takes a lot of time too.
What problems are you solving with the product? What benefits have you realized?
Reporting, Data Analytics, Data Manipulation, Advanced Analytics and Prediction
Recommendations to others considering the product:
Good tool to learn Data Analytics and disseminate the knowledge within the company, however its best to learn Python / R additional to KNIME to be capable of everything within KNIME.


    Zachary B.

Using Knime for quick data science experiments

  • April 25, 2019
  • Review verified by G2

What do you like best?
The program offers a vast amount of optionality for being able to create data science/analytics models without writing any code. It's very quick and easy to use.
What do you dislike?
It can be difficult to find certain functionalities within the program. Additionally, it does struggle with larger datasets and seem to choke
What problems are you solving with the product? What benefits have you realized?
We use Knime for quick experiments to determine what type of model we will build, how it will be built and have a rough approximation for performance
Recommendations to others considering the product:
I have enjoyed using this product, Knime, more so than SAS, RapidMiner and other similar visual analytics BI platforms


    Hospital & Health Care

Used it for etl, data cleansing, data preparation and analys

  • April 09, 2019
  • Review verified by G2

What do you like best?
It’s capabilities to quickly sourcing data , preparing it and making it analytical rrasy
What do you dislike?
It’s not scaled for larger data sets. It slows down or sometimes even crash. Also it won’t integrate with all the database providers
What problems are you solving with the product? What benefits have you realized?
Cash flow , data quality issues , finance forecasting


    Monica M.

Great app. Just some anotations

  • March 06, 2019
  • Review verified by G2

What do you like best?
The capability to design a big amount of tasks with the software, covering the proccessing of the information all way down.
What do you dislike?
Some of the options are not exactly what i used to need to proccess the information. The fluxes have (on a certain way) a limited amount of configuration options.
What problems are you solving with the product? What benefits have you realized?
At my place i use it to proccess the clients information to get some knowledge about the behaviour.
Recommendations to others considering the product:
Is a great option to get Knowledge from the information that goes all over your company 24/7


    Information Technology and Services

Intuitive and effective tool for data analytics

  • November 05, 2018
  • Review provided by G2

What do you like best?
Drag and drop analysis helps faster and effective analysis flow. Graphical user interface makes it easy to plan processes and organize projects. You can work together with teams at the same time.
What do you dislike?
Lack of technical support in the free version. Costing needs to be more economical.
What problems are you solving with the product? What benefits have you realized?
Workflow analysis is made simpler and effective with KNIME. We can use it with Python and R as well as integration with Weka.
Recommendations to others considering the product:
Highly effective and easier than other alternatives such as Rapid Miner.


    E-Learning

User Friendly, Audit Friendly

  • October 29, 2018
  • Review verified by G2

What do you like best?
- Data wrangling is easily manageable
- Clear cut motions for running different models and exporting results
- Lots of different applications
- Drag and drop functionality rocks
What do you dislike?
- R function is hard to bring in
- Data / findings output formatting needs to be updated for presentations
What problems are you solving with the product? What benefits have you realized?
- Sentiment Analysis--> Seamless audit
- Predictive Modeling
- Keeping different analyses in one place without having to parse through code