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XLMiner is a software that has been widely praised by users for its analytical capabilities and its usefulness in solving complex queries. …
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What is Analytic Solver?
Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
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What is Analytic Solver?
Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
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What is Analytic Solver?
Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
Analytic Solver Video
A short overview of the Ribbon and Task Pane interface in our Excel Products including: Analytic Solver, Risk Solver, Premium Solver, and XLMiner. See the "Building your first optimization/simulation model" example videos for more detailed.
Analytic Solver Technical Details
| Operating Systems | Unspecified |
|---|---|
| Mobile Application | No |
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XLMiner is a software that has been widely praised by users for its analytical capabilities and its usefulness in solving complex queries. It has been utilized in various fields, including data analytics for research purposes and academic settings like ISB. Reviewers have mentioned that the software has played a significant role in improving corporate performance by assisting employees in enhancing their existing models. Users have found the software to be highly beneficial for data preparation, offering valuable insights, and performing complex calculations with its built-in functions.
One of the standout use cases of XLMiner is its ability to make predictions, particularly in solving transportation problems, which saves users considerable time. Additionally, it has been extensively used for training data sets and machine learning, enabling users to enhance their understanding of data science concepts. XLMiner's capabilities also extend to statistical analyses and sales modeling, making it a valuable tool for individuals in the analytics field or those looking to build a career in analytics without coding knowledge.
Moreover, users have leveraged XLMiner for diverse needs such as gathering insights from diabetic patient data in hospitals, analyzing large datasets, and creating alloys by blending scrap. The software has also proven valuable for optimizing solutions, testing hypotheses, and forecasting with simple Excel data, eliminating the need for coding and saving time. Its seamless integration with Excel and its ability to handle high complexity have received praise from reviewers.
Analytic Solver, a component of XLMiner, has been notably useful for solving MINLP cases and providing near-optimum solutions that can be further manipulated by users. Users have harnessed Analytic Solver's capabilities for simulation optimization and expressed interest in exploring other functionalities such as stochastic programming. While the cost can be prohibitive for some due to complexity or scale, Analytic Solver remains an invaluable tool across industries.
In summary, XLMiner caters to a wide range of use cases such as research analytics, academic applications, corporate performance improvement, data preparation and analysis, prediction modeling, statistical analysis, machine learning, and optimization. It has proven useful in various sectors like healthcare, manufacturing, and education, offering valuable insights and efficient solutions to complex problems.
Smooth and Precise Working Process: Reviewers have described the working process of the system as smooth and precise, with accurate results. Several users have mentioned that they appreciate the efficiency of the system in providing reliable outcomes.
User-Friendly Interface: The interface of the product has been praised by many users for being user-friendly and easy to navigate. Multiple reviewers have highlighted that the intuitive design makes it simple for both novice and experienced users to operate without any difficulties.
Ease of Use Without Coding: Users have appreciated the ease of use provided by the product, stating that even individuals without expertise in data science or machine learning can perform tasks such as data analysis and predictions. Many reviewers specifically mentioned that they like how XLMiner allows them to perform these tasks without requiring coding skills.
System Lag: Several users have expressed frustration and irritation due to the system lag when processing heavy data. This lag can cause significant delays in their work, leading to decreased productivity and increased frustration. Lack of Awareness and Knowledge: Some users have complained about the lack of awareness and knowledge surrounding XLMiner. They believe that XLMiner is an underutilized software with untapped potential. Many users are not aware of its capabilities or how to fully utilize it, which limits their ability to leverage the software for advanced data analysis tasks. Limited Handling of Large Datasets: Users have noted that XLMiner has limitations when it comes to handling large datasets compared to other tools like R or Python. The software may struggle with processing and analyzing extensive amounts of data efficiently, which can be a significant drawback for those working on complex data analysis projects.
Users have made several recommendations based on their experience with the software. They recommend using the software as it solves analytics problems from A-Z in one go. It is considered a good tool for mining smaller datasets and performing statistical analysis and machine learning algorithms. Some users suggest using XL miner as a stepping stone to understanding data mining before moving on to more advanced programming languages like Python or R. They find it beginner-friendly and helpful for gaining foundational knowledge in data mining. To get up to speed with the software, users suggest watching instructional videos that provide guidance and instructions on how to effectively use its features and functionalities. Overall, users find the software useful for completing data analytics tasks quickly and easily, especially for beginners in the field of data mining and those working with small datasets.
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December 11, 2018
Excellent complementary analysis tool for Excel users.
Basically the software has been used in applications associated with the optimization of network models that qualify in the category of transport and transshipment models.
This type of models as well as others like the WinQsb are basically used by the department that is under my supervision, and are not commonly used in the organization.
The last situation in which it was implemented was to try to model part of the hydrographic network of the Peruvian Amazon where the nodes of the network were possible locations of fuel supply sites, rotation of personnel and raw material proper to the activity that it was modeling, trying to optimize (minimize) the total costs associated with this activity, which were a function of the relative location existing between the potential nodes.
This type of models as well as others like the WinQsb are basically used by the department that is under my supervision, and are not commonly used in the organization.
The last situation in which it was implemented was to try to model part of the hydrographic network of the Peruvian Amazon where the nodes of the network were possible locations of fuel supply sites, rotation of personnel and raw material proper to the activity that it was modeling, trying to optimize (minimize) the total costs associated with this activity, which were a function of the relative location existing between the potential nodes.
Different scenarios were simulated where not only the location but the number of eventual nodes were varied, and also different sensitivity analyzes were carried out in order to evaluate their impact on the selected options.
- Without the program being "my favorite" it is necessary to recognize that handling in the Excel application environment provides it with a feature with a high added value, compared to other softwares that do not have those characteristics, which makes the handling of data from external sources is easier.
- In addition to its inherent quality of general data analysis, I can also highlight the areas in which I have used it (field of linear optimization, simplex method and non-linear optimization, network models) where it has allowed me to model, simulate and analyze different situations with great success.
- I could say that the limitations are not the program but mine as a user of it.
- Unlike other software that I have used (WinQsb and Lingo, for example), it presents an acceptable customer service.
- On the few occasions when I have used it to deal with problems of optimization of relatively large parameters (with a large number of restrictions and decision variables), the program has been slower, not substantially but slower, than programs such as the WinQsb, even when the latter runs on 32-bit machines and not 64. That has caught my attention, even though it is not a real problem for the uses I give to the program.
- Given my partial function as a university professor, it has been much more effective and practical to use other software, due to the limited options that the educational license associated with the software has.
- - It has allowed finding ways to optimize (minimizing costs or times) the field processes involved in various projects.
- It has even allowed, in specific cases where it was used for that purpose, to optimize the allocation of resources (people) to work in different jobs that present weekly variations of the activity that these people must perform.
- It has allowed the sensitivity analysis of projects to changes in the decision variables related to them, which, and in very dynamic and changing environments, resulted in substantial decreases in money losses.
The use of this software does not necessarily follow that it is "globally better" than others. In the department we have used this and others with similar characteristics, given that, as previously indicated, all the software has advantages and weaknesses with respect to other software with similar characteristics. Obtaining better results lies in the user's ability to detect those "benefits and weaknesses" and maximize their usefulness within the specific field of work in which they operate.
In our case, one of the reasons that led us to try and use it, was related to trying to "tie" more processes to the same environment, which in this case is the one associated with the Excel database, in such a way as to reduce the initial manipulation and accommodation that should be made to the data if they come from different sources such as MATLAB, or WinQsb.
This facilitates the use of software for the type of user who does not necessarily have deep knowledge of linear algebra or operations research, for example.
In our case, one of the reasons that led us to try and use it, was related to trying to "tie" more processes to the same environment, which in this case is the one associated with the Excel database, in such a way as to reduce the initial manipulation and accommodation that should be made to the data if they come from different sources such as MATLAB, or WinQsb.
This facilitates the use of software for the type of user who does not necessarily have deep knowledge of linear algebra or operations research, for example.
On the contrary, the most analytical and knowledgeable user manifested in a high percentage, preferring to use MATLAB as a tool, claiming that they have a greater and easier access to the calculation functions, which even in specific cases, could be modified.
October 27, 2017
Simple & Easy Solver for optimization
My organisation is using it for optimization problems related to raw material and finished goods for their shipments and production planning purposes. It is used only in my function- sales and operations planning. This tool is useful for the company who wants to build the optimization model in Excel for quick strategic and tactical decisions. Solver is easy to understand and learn. My company is using Solver for product optimization, manufacturing plan and raw material planning. It helps busineses to understand the financial estimates across the distribution network. It helps to provide the feasible solution for production to produce what product at what location in an optimized manner.
- Easy to use and learn.
- Strong optimization platform for business and supply chain problems which can be modeled in Excel
- It can handle multiple objectives and more than 8000 decision variables in a problem.
- Lots of tutorial and examples are available to solve the problem
- Can not handle stochastic modelling
- Difficult to work on the non-linear program
- Managing the data is difficult using the big models in the tool
- Excel Solver and Lingo
We believe in building the models in Excel. A limitation with Excel is that Excel Solver can not take more than 200 decision variables with multiple constraints. It is cheap in terms of license and maintenance fees against other softwares which are available in the market.