Looker Studio vs. Maple vs. Wolfram Mathematica

Visualizing cross-channel campaign performance can blend data from a few different sources to compare performance metrics like spend, clicks, and conversions side-by-side in a single view, which helps in quick budget reallocation decisions. When dealing with massive volumes of data (millions of rows) or highly complex queries, Looker Studio dashboards can become slow, laggy, or even crash. Performance issues are a frequent complaint when working with large datasets, making it unsuitable for enterprise-level companies

Incentivized

Maple is very useful in following scenarios :

• When doing some equation modelling for differential equations
• Writing code to simulate a electrical of mathematical system
• Speech and Image Processing Use case
• Linear Algebra Problems
• Lot of Options to plot 2-D and 3-D, including implicit, contour, complex, polar, vector field, conformal, density, ODE, PDE, and, statistical plot
• Engineering plots, including time and frequency domain responses and root-locus and root-contour plots

Incentivized

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.

• Breath of data - the number of ways to interrogate the data is endless, and the options to view metrics alongside each other make for comprehensive datasets.
• Data visualisation and customisation - the options for presenting data and separating out across pages allow for clean visuals and segmented information.
• Easy shareability/usability - a quick and simple tool to introduce colleagues to, and easy to grant access for them to be able to view the data, without having to understand the setup itself.

Incentivized

• Numerical Calculation and Calculus
• Visualization of statistical and numerical data
• Predefined code templates for standard problem like finding FFT

Incentivized

• 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.

Incentivized

• It needs better handling of complex logic. We often need workarounds to perform complex custom calculations, and it can be really unpleasant at times.
• Felt it got slow with a larger data set, and in one minor report, we had to set up time filters so that calculations during spikes could be traced more quickly.
• Compare to competition they need to improve with notification things.

Incentivized

• On the software side and the software is bulky
• Code Editor can be improved
• Sometime software fails and hang when doing high calculation

Incentivized

• 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.

Incentivized

It is the simplest and least expensive way for us to automate our reporting at this time. I like the ability to customize literally everything about each report, and the ability to send out reports automatically in emails. The only issue we have been having recently is a technical glitch in the automatic email report. Sadly, there is almost no support for this tool from Google, but is also free, so that is important to take into consideration

Incentivized

Looker Studio is easy to use, and it offers a sufficient variety of predefined visualizations to choose from. It's easy for us, and anyone can set up basic reporting without extensive data visualization skills. The interface layout is easy to understand, and it doesn't take long to get used to.

Incentivized

I give it a lower support rating because it seems like our Dev team hasn't gotten the support they need to set up our database to connect. Seems like we hit a roadblock and the project got put on pause for dev. That sucks for me because it is harder to get the dev team to focus on it if they don't get the help they need to set it up.

Incentivized

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.

Incentivized

Looker Studio is far easier to implement, stand up, and learn. The interface is simpler and user-friendly for various levels of data visualization/analysis knowledge and experience. The biggest benefit of Looker Studio, however, is its ease of connection to GA data and speed. Furthermore, since it is an online program/tool, it requires less CPU/battery/storage on the user's device.

Incentivized

Maple is a very niche product and competes directly with Mathematica and MATLAB. It is a little expensive as compared to the other two however has more set of functions and libraries which makes it for suitable for high level and complex mathematics. It's editor is not on par with other two however it's visualization module is very good and powerful.

Incentivized

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.

Incentivized

• Free, so the only investment is time
• Because it doesn't have native support of non-Google sources, it can cost more money than Tableau
• The time spent formatting the templates or building connectors can have a negative impact on ROI
• As a agency, charging for the reporting service is profitable after the first month or two after building the dashboard.

Incentivized

• It saves time and does lot of hard calculation which is not possible manually
• Software is little bit expensive however has more functions as compared to Matlab and Mathematica
• Learning curve is little steep and hence take additional time to master

Incentivized

• 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

Incentivized