Likelihood to Recommend 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.
Rob Blanford Artificial Intelligence & Machine Learning Manager
Read full review If you have an analytics department, Data Science is perfect for making analyses quicker. Data Science works well for web querying, automating analyses, sharing advanced analyses with others, and performing lots of other advanced analytical processes. Data Science is not a good fit if the analytics you do is stuff that Excel can do. The software is powerful, with lots of features, and unless you actually plan on using those features, it's not worth paying for.
Read full review Pros 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. Read full review It has a great user interface, easy to navigate and learn on the fly. There are lots of great options for data organization and analysis! Makes it a handy tool for presentations as well. A collaborative ability is highly valued for my company where we often work from home or on site. Being able to share the data with those in the office so multiple people can look at it is a great tool! Read full review Cons 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. Read full review Unfortunately, some functionality is hidden per upgrade to other versions. Feel data mining functionality would be useful, but not budget for software. At the current price point, would have expected more (such as Mathematica breadth of functionality for one price). It is light on optimization capability. Slow when considering very large datasets, performing things such as distribution identification Steve Wagner Director, Network Design and Logistics Analytics
Read full review Likelihood to Renew 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
Read full review The company is hesitant to spend this much on software. They are primarily an engineering firm, and they don't understand the use of analytical software for environmental professionals.
Read full review Usability 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
Read full review Support Rating 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.
Ivan Cui Data Scientist - Biotech Data Science Digtialization (BDSD)
Read full review Implementation Rating 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.
Read full review Alternatives Considered 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].
Read full review I prefer Spotfire Data Science's approach. It is more natural and fits the way I think. I prefer to use Spotfire Data Science's VB for writing macros. It is real code, meaning that I do not need to trick the software to do what I need and there are no implied loops over solving simple problems. The graphs are publication quality and can be edited by hand or using a macro if I am building hundreds of them. Spotfire Data Science had a user-friendly approach to building lengthy data processing streams (in its workspaces). It is just so fast for analyzing a dataset that you have never seen before and efficient for ongoing work on the same data.
Read full review Return on Investment 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. Read full review Our company has had the program for less than 1 year. We don't expected a positive return this year. The goal is for Data Science to led to defined projects by the end of the end of the year and implementation in the following two. Overall, we are planning on 4 years to fully recoup the cost of the software and the cost of implementing identified projects. Read full review ScreenShots KNIME Analytics Platform Screenshots Spotfire Data Science Screenshots