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.
I don't really know another program as powerful as Excel. I've used Google Doc programs but do not feel they come close. So far, anytime I've needed a table of some sort for data, whether it's budget oriented or information off a survey, the best system has been Excel. We do web audits on occasion and we create an Excel worksheet featuring every URL of the pages we're auditing, notes, data about the content, information about files attached to the page and other information to help us determine what pages need updating, deleting or otherwise. We also use Excel primarily to export our Google Analytics to in order for us to create reports for clients that need to see specific information about their traffic.
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.
Excel offers collaboration features that allow multiple users to work on the same spreadsheet, but managing changes made by different users can be challenging. Excel could improve its features by offering more granular control, better tracking of changes, and more robust conflict resolution tools.
Itcan be a barrier to productivity when importing and exporting data from other applications or file formats. To improve its features, it should offer better support for standard file formats and more robust error handling and reporting tools.
Excel can be challenging for finance students and working professionals, but it can be improved by offering more robust tutorials, better documentation, and more user communities and support forums.
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
Excel remains the industry standard for spreadsheets and has maintained simple and straight-forward formula writing methods. Although there is a learning curve to do more complex calculations, there are countless help sites and videos on the Internet for almost any need.
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
I'm giving it a 7 because it is my go to. But the fact other prefer Google Sheets when working with a team does get irritating. I've used the online version of Microsoft Excel that other teams can get into and it still seems behind Google Sheets. It's a little clanky and slow? If that's even a term.
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].
Out of Microsoft Excel, Microsoft Power BI, IBM SPSS, and Google Sheets, Microsoft Excel is by far the most common tool used for anything data-related across organizations. Accordingly, our organization has also implemented Microsoft Excel as a first-step tool. We recently adopted Microsoft Power BI (the free version), and use it occasionally (mostly for creating dashboards), but it is less commonly understood by stakeholders across our organization and by our clients. Accordingly, Microsoft Excel is more user-friendly and because of its popularity, we can easily look up how to do things in the program online. Google Sheets is a comparable alternative to Microsoft Excel, but because it's cloud-based and we have sensitive data that needs to be protected, we chose against using this software. Finally, a few users (including myself) have access to and utilize IBM's SPSS. For my role, it's a helpful tool to do more rigorous analyses. However, because of its cost and limited functionality as a simple spreadsheet, we only use it for more complex analyses.
Each user can use it to whatever level of expertise they have. It remains the same so users can contribute to another's work regardless of whether they have more or less expertise
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.
