One significant improvement is its speed. With KNIME, you can accomplish many tasks in a single day. It's very fast since you mostly work with prebuilt nodes and libraries. Also, the latest version allows us to add Python code if needed.

One way KNIME has improved our organization is by allowing us to perform analyses that we previously couldn't. We often start with data in Excel or CSV format, and the process of importing data from other software, such as SPSS or STATA can be challenging. With KNIME, the process is simplified, as we can easily import the data with a single node, making it quick and efficient.

The solution has improved our company because it is economical as it is an open-source platform. There are not a lot of costs involved.

It is a free open-source tool that performs very similarly to other expensive tools. KNIME has been great for me over the years. It allows me to connect to various sources including data warehouses, then put the processing logic together (ETL-like), which can be quite complex and produce the required output. Ultimately, it would go into Excel or Tableau for presentation.

KNIME has improved our organization because we are able to collect data in a way that we can interpret and it provides visuals.

NA

In addition to leveraging KNIME flexibility to query data from our database for ad-hoc business cases, the product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine. In some particular cases, my team builds the workflow and then we hand it over to the stakeholder, who can run it on his own by inserting a variable or changing a few settings in the workflows.

I had been doing this via a mix of Excel macros and some things by hand. Even with the macros, it would take me 30-plus minutes every week, and even that was just for the raw data to get to pivot tables. If I wanted additional calculations based on pivot table data, that would take even more time. With KNIME, I am able to get that process down to under one minute, with data broken down into individual tabs. It has changed my week.

It gives much insight about business in different aspects, from understanding product portfolio to clients, much of them arouse interests from important stakeholders

While the product has not yet improved our organization, we expect to use it in full deployments with our clients to greatly reduce their costs and make our services more attractive.  

My organization's field of activity is to develop business applications for niche areas. Almost three years ago, we decided to extend our solutions with advanced analytics. KNIME let us start easy and fast into the Advanced Analytics area. We are able to try project ideas with KNIME by doing proof of concept easy and prototyping fast.

KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data.

It has allowed us to easily implement advanced analytics into various processes.

It very much helps me to do my job while supporting my organization's delivery of service to our client.

The clients I performed the analyses for were all very pleased with the results. For churn prediction, one of the companies proactively started contacting clients with high risk to churn, resulting in drastically decreasing churn rates.

For organizations with a small team of data analysts or data scientists, it is a very easy tool to become familiar with predictive modeling, and makes it possible to hand over projects to colleagues without the need to extensively document them.

We are able to automate several functions which were done manually. I can integrate several data sets quickly and easily, to support analytics.

We are far from reaping the benefits of this platform as an organization. However, so far, we have been able to appreciate the considerable reduction in prototyping time.

Lot of manual work has been automated through this and single solution created on this can be used by others, too. We have implemented the same thing in our organization as CAE.

We have use it in industry projects, for internal experiments, and for teaching.