KNIME Analytics Platform vs. Kortical

KNIME Analytics Platform is excellent for people who are finding Excel frustrating, this can be due to errors creeping in due to manual changes or simply that there are too many calculations which causes the system to slow down and crash. This is especially true for regular reporting where a KNIME Analytics Platform workflow can pull in the most recent data, process it and provide the necessary output in one click. I find KNIME Analytics Platform especially useful when talking with audiences who are intimidated by code. KNIME Analytics Platform allows us to discuss exactly how data is processed and an analysis takes place at an abstracted level where non-technical users are happy to think and communicate which is often essential when they are subject matter experts whom you need for guidance. For experienced programmers KNIME Analytics Platform is a double-edged sword. Often programmers wish to write their own code because they are more efficient working that way and are constrained by having to think and implement work in nodes. However, those constraints forcing development in a "KNIME way" are useful when working in teams and for maintenance compared to some programmers' idiosyncratic styles.

Incentivized

Kortical is really widely applicable to many use cases, although it doesn't handle images or video it is great to help you build really great ML models without needing to plan ahead what you are going to try, you let the platform build you the best model. It is suited to beginner and more advanced data scientists as you can edit the code to narrow the search space which makes model creation more you build it without AutoML. Hosting the model behind an API that is ready to go is great as it saves so much time vs doing that dev work from scratch

• Summarize instrument level financial data with relevant statistics
• Map transactions from core extracts to groups of like transactions using rule engines
• Machine learning using random forests and other techniques to analyze data and identify correlations for use in predictive models
• Fill out sampling data from averages.

• The NLP models results were much better than the ones that we did outside of the platform.
• It is really easy and quick to build a good model with a lot of the manual boring tasks all done automatically like one hot encoding, etc.
• Kortical shows the features and their importance for any model type as part of the platform which is great for understanding the models.

• It does not have proper visualization.
• Some other BI tools (QlikView) have much easier functions for data interaction.
• Some other BI tools (Tableau) can be set up much faster.
• It is not an easy tool to use for non-tech savvy staff.

Incentivized

• It would be ideal to have Jupyter built into the platform, they say it is coming.
• Also while it is easy to use, at the start it would have been helpful to have more help guides.

We are happy with Knime product and their support. Knime AP is versatile product and even can execute Python scripts if needed. It also supports R execution as well; however, it is not being used at our end

KNIME Analytics Platform offers a great tradeoff between intuitiveness and simplicity of the user interface and almost limitless flexibility. There are tools that are even easier to adopt by someone new to analytics, but none that would provide the scalability of KNIME when the user skills and application complexity grows

Incentivized

KNIME's HQ is in Europe, which makes it hard for US companies to get customer service in time and on time. Their customer service also takes on average 1 to 2 weeks to follow up with your request. KNIME's documentation is also helpful but it does not provide you all the answers you need some of the time.

Incentivized

Their support is great as we use Slack and we have our own channel and they always respond really quickly. Data Science support is available to help unblock you as well as dev support as we're setting up the data feeds. It would be great if there were more FAQ or self-help guides in the platform but the personal touch is also really appreciated and probably gets us there quicker anyway.

KNIME Analytics Platform is easy to install on any Windows, Mac or Linux machine. The KNIME Server product that is currently being replaced by the KNIME Business Hub comes as multiple layers of software and it took us some time to set up the system right for stability. This was made harder by KNIME staff's deeper expertise in setting up the Server in Linux rather than Windows environment. The KNIME Business Hub promises to have a simpler architecture, although currently there is no visibility of a Windows version of the product.

Incentivized

Having used both the Alteryx and [KNIME Analytics] I can definitely feel the ease of using the software of Alteryx. The [KNIME Analytics] on the other hand isn't that great but is 90% of what Alteryx can do along with how much ease it can do. Having said that, the 90% functionality and UI at no cost would be enough for me to quit using Alteryx and move towards [KNIME Analytics].

Incentivized

• It is suited for data mining or machine learning work but If we're looking for advanced stat methods such as mixed effects linear/logistics models, that needs to be run through an R node.
• Thinking of our peers with an advanced visualization techniques requirement, it is a lagging product.

Incentivized

• ROI is great as what we would spend on compute we get the AutoML for essentially the same price so it is cost neutral as Kortical comes with compute built-in.
• The results mean that we can automate so much more than our previous model so that is key to the positive ROI.
• The platform auto trains new models and lets us know when there is a better model so it has saved a lot of time so we can focus on new business problems to solve with ML.