Microsoft Excel vs. Wolfram Mathematica

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.

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We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.

Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.

• 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.

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• It allows straightforward integration of analytic analysis of algebraic expressions and their numerical implemented.
• Supports varying programmatic paradigms, so one can choose what best fits the problem or task: pure functions, procedural programming, list processing, and even (with a bit of setup) object-oriented programming.
• The extensive and rich tools for graphical rendering make it very easy to not just get 2D and 3D renderings of final output, but also to do quick-and-dirty 2D and 3D rendering of intermediate results and/or debugging results.

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• Counting conditionally formatted cells (e.g., you have 5 green cells, 10 red ones, and 3 orange ones in a row).
• Merging cells in a table; I have to remove the table first and then re-add the table to merge cells together.
• Offering more preset colour categories for formatting graphs.
• Built-in functions to run ANOVAs, Multiple Linear Regression, Factor Analysis, etc.

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• Should include more libraries and functions.
• Should include more functions that can be used in Machine Learning.
• Should include more functions that can be used in Data Science.

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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.

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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.

I have rarely, if ever, had issues with its availability.

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Again it does what I need it to do with little to no issues.

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I have not had to use it often, but it is good.

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Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.

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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.

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We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models. Mathematica compares favorably to this alternative in terms of speed of development. Mathematica compares unfavorably to this alternative in terms of license costs.

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N/A I was not involved in this process.

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It integrates well with all cross functional teams

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• Excel has positively impacted the business as it has increased our efficiency.
• It also saves us the time that we would have spent on making the calculations that it does for us.
• Since it works on all devices and is compatible with both Windows and Mac, we do not have to invest in any other alternative.

• Easy to solve huge mathematical equations, so it saved time there
• Doing analysis and plotting graphs is also another plus point
• Learning is very slow, and it took lot of time to learn its scripting language

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