We performed a comparison between KNIME and Microsoft BI based on our users’ reviews in four categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: KNIME is a great alternative for organizations that are looking for a cost-saving, flexible, stable solution to handle their Data Mining and Data Science needs. Microsoft BI is a comprehensive, robust solution that performs well with Data Mining and Data Science in addition to exceptional performance as a Business Intelligence (BI) tool. As many PeerSpot users are heavily invested in the Microsoft ecosystem, Microsoft BI is the consistent trusted choice.
"The solution allows for sharing model designs and model operations with other data analysts."
"The solution is good for teaching, since there is no need to code."
"I was able to apply basic algorithms through just dragging and dropping."
"Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time."
"It's a huge tool with machine learning features as well."
"Overall KNIME serves its purpose and does a good job."
"It also has very good fundamental machine learning. It has decision trees, linear regression, and neural nets. It has a lot of text mining facilities as well. It's fairly fully-featured."
"KNIME is quite scalable, which is one of the most important features that we found."
"The solution is easy to set up and implement."
"It is stable enough. It has a lot of powerful functions. It can also be customized with the DAX language. It is also intuitive enough and incremental. You can start with something simple, and then step-by-step, you can increase the reports and dashboards according to your needs."
"The most valuable feature is definitely the visual aspect and the DAX capabilities to virtually do anything."
"The way data is presented is very valuable. The amount of information that we can get at a glance is also valuable. You can then drill-down and see data from many different angles in the same chart by selecting certain things. Based on the selection, everything changes automatically. If we have four parameters in a particular item, when you select a parameter, the remaining charts on that page automatically change for that particular parameter."
"What I have found valuable about Microsoft BI is its performance and ease of use. The interface is very simple and it is accessible to everyone. If someone is new to this type of solution it is straightforward to understand."
"It's a very easy-to-use solution."
"Microsoft BI allows us to connect to any database or any dataset."
"Power BI is a complete ecosystem. It has an integrated ETL tool and good connectivity with applications such as Office 365 and SQL. There are also solutions for RPA, such as Microsoft Power Automate and Microsoft Power Apps. Power BI now has integration with Power Query, which has an AI feature for text analytics. Text analytics is a very good feature. This feature is also there in Tableau, but I like it in Power BI because you can write something like, "What is the total sale in the Eastern region?", and it will give you the answer. For example, when you have different types of user opinions, you just run one algorithm and you will have the output that provides the number of positive and negative responses. You can even have a dashboard with positive remarks. This feature has been introduced recently. Power BI supports the DAX and Power Query M languages. These languages are making Power BI very strong in data analytics, and you can do many types of analysis."
"It's very general in terms of architecture, and as a result, it doesn't support efficient running. That is, the speed needs to be improved."
"KNIME could improve when it comes to large data markets."
"Compared to the other data tools on the market, the user interface can be improved."
"There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger."
"The license is quite expensive for us."
"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."
"I would prefer to have more connectivity."
"KNIME is not scalable."
"Capacity could be improved."
"The solution could use a faster speed on certain interactions and a refresh of the dashboards."
"They are improving it all the time. What would be nice is if they could respond to feature requests more quickly. They can provide faster support for new features."
"The reporting could be a bit better."
"Power BI could have better metadata management. It's easy to use for a single person. However, it lacks an enterprise-grade metadata management system, which can be a problem if you're doing an enterprise deployment with multiple users."
"When there are large amounts of data being processed there are additional tools needed to handle it."
"The UI is the main improvement that could be made. Specifically, there is something called DAX, in Power BI, which is complicated compared to calculated fields used in Tableau."
"In Microsoft Excel, you are able to have tabs. However, in Microsoft BI you do not have this flexibility."
KNIME is ranked 1st in Data Mining with 16 reviews while Microsoft BI is ranked 1st in BI (Business Intelligence) Tools with 152 reviews. KNIME is rated 8.0, while Microsoft BI is rated 8.0. The top reviewer of KNIME writes "Allows you to easily tidy up your data, make lots of changes internally, and has good machine learning". On the other hand, the top reviewer of Microsoft BI writes "A complete ecosystem with an builtin ETL tool, good integrations with python and R, and support of DAX and Power Query (M languages)". KNIME is most compared with Alteryx, RapidMiner, Weka, Microsoft Azure Machine Learning Studio and Dataiku Data Science Studio, whereas Microsoft BI is most compared with Amazon QuickSight, Tableau, Oracle OBIEE, Domo and MicroStrategy.
We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
