Grow, from Epicor since the March 2022 acquisition, is a business intelligence software that is designed to empower businesses to become data-driven and accelerate growth by aligning team objectives and inspiring strategic decisions.
N/A
Mathematica
Score 8.2 out of 10
N/A
Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.
$1,520
per year
Pricing
Epicor Grow
Wolfram Mathematica
Editions & Modules
No answers on this topic
Standard Cloud
$1,520
per year
Standard Desktop
$3,040
one-time fee
Standard Desktop & Cloud
$3,344
one-time fee
Mathematica Enterprise Edition
$8,150.00
one-time fee
Offerings
Pricing Offerings
Epicor Grow
Mathematica
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Required
No setup fee
Additional Details
—
Discounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
Grow.com is well suited if you have a lot of data or client data to manage. If you do not have tons of data, there are other options out there that are a bit more simple and easy to use and a better price.
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.
I love the fact that you have a team of developers who can help me build metrics or fix metrics that I do not create properly. I had to learn SQL in order to really build the metrics that mattered, which was a lot of fun, but resulted in many broken metrics. The vendor's team was great in responding to me requests for help!
Really, really appreciate the fact that Grow has SQL formulas to reference when building metrics. Again, as a novice, this accelerated my ability to learn and not have to leave your site and resources and stay within the Grow web properties.
Great account managers who check in regularly and are willing to help out whenever needed.
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.
Grow.com is structured in [...] such a way that it is easy to get started for individuals that known SQL. For individuals that are not as well versed at SQL, the learning curve is much steeper. In such cases, it would be better for users to learn SQL and then go for data visualization with Grow.com.
If there is one area that Grow.com excel[s] upon much better than other data visualization tools, it is Grow.com's customer/tech support. Grow.com responds much quicker and does a better job of getting to a solution [than] any other business intelligence tool on the market. The support staff gets the big picture [...] and knows how to help.
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.
Grow doesn't have as many advanced analytics features and other capabilities as some other 'dashboard' platforms on the market. Simply, if you want a tool for internal use only that has high-level analytics capabilities (regressions, completely custom visualizations, modeling), Grow probably isn't the platform for you. To put it another way, if you have a team of data engineers and scientists doing complex analysis, Grow might not make the most sense. However, if you understand the value of data/visualization/dashboards, but lack some of those skillsets in your company, Grow might be the perfect fit. Not only is it incredibly scalable and reasonably priced compared to other market solutions, but their transform capabilities really stand out. They have many native data transformations that mimic SQL coding of a dataset, without requiring any knowledge of SQL. They've converted these transformations to easy-to-use tools in the platform, which are perfect for the less-technical user.
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.
