KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.
$0
per month
Microsoft Excel
Score 8.9 out of 10
N/A
Microsoft Excel is a spreadsheet application available as part of Microsoft 365 (Office 365), or standalone, in cloud-based and on-premise editions.
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.
For tasks like financial analysis, budgeting, forecasting, and data visualization, I frequently use Microsoft Excel. I can develop financial models, use pivot tables to examine enormous datasets, and produce eye-catching visualizations thanks to its comprehensive features. I have, however, also come across circumstances in which Excel isn't the best tool.Excel falls short of alternatives like Google Sheets when I need to collaborate with my team in real-time. I favor employing robust database management systems or data analysis tools like SQL, Python, or R for managing very big data sets or sophisticated calculations. I use specialized tools like SPSS, SAS, or programming languages for better outcomes when complex statistical analysis or machine learning are necessary. And finally, for formatting elaborate reports, In conclusion, even though I consider Excel to be a great tool for many finance jobs, there are some limits in collaborating, processing big amounts of data, performing complex analysis, and creating documents that I take into account when choosing the best tool for the job.
It is very good at embedded formulas and tying cells to one another
It allows me to compare deals terms on a side-by-side basis and talk my clients through it easily.
It is very helpful as well in terms of allowing me to filter/sort results in many different ways depending on what specific information I am most interested in prioritizing.
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
It comes with MS Office. Unless we stop using PCs or Microsoft Office, it's highly unlikely, even imperceivable to not continue to use Excel. It would be nice to see more Excel functions used, though, beside basic tables and calculations.
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
Microsoft excel stands out in its User Interface as compared to any other software which offers same functionality. It can be used by a beginner as well as the expert in the same field. It is having many features as we dig deep in it like advance functions, dynamic arrays, pivot, VBA and Macros.
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.
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.
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].
We utilize Tableau and Alteryx in addition to Excel. We use Excel since we have a data dump that could be utilized in feeding for these two solutions. We select Excel for some manual work then plug the data into the other two tools for further analysis around text analytics like word clouds in Tableau, or text mining in Alteryx. Excel is an input data source that we use in conjunction with these two.
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.
