Frontline Systems Analytic Solver is an Excel add-on for performing data mining, and predictive analytics from within Microsoft Excel.
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IBM InfoSphere Information Server
Score 8.0 out of 10
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IBM InfoSphere Information Server is a data integration platform used to understand, cleanse, monitor and transform data. The offerings provide massively parallel processing (MPP) capabilities.
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Pricing
Analytic Solver
IBM InfoSphere Information Server
Editions & Modules
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Offerings
Pricing Offerings
Analytic Solver
IBM InfoSphere Information Server
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Analytic Solver
IBM InfoSphere Information Server
Features
Analytic Solver
IBM InfoSphere Information Server
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Analytic Solver
-
Ratings
IBM InfoSphere Information Server
8.7
4 Ratings
6% above category average
Connect to traditional data sources
00 Ratings
9.94 Ratings
Connecto to Big Data and NoSQL
00 Ratings
7.54 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Analytic Solver
-
Ratings
IBM InfoSphere Information Server
9.6
4 Ratings
17% above category average
Simple transformations
00 Ratings
10.04 Ratings
Complex transformations
00 Ratings
9.24 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Analytic Solver
-
Ratings
IBM InfoSphere Information Server
8.0
4 Ratings
2% above category average
Data model creation
00 Ratings
8.72 Ratings
Metadata management
00 Ratings
7.74 Ratings
Business rules and workflow
00 Ratings
8.44 Ratings
Collaboration
00 Ratings
8.04 Ratings
Testing and debugging
00 Ratings
7.14 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Based on my limited experience and use, and therefore limited global knowledge of the software, I would recommend it especially if the data that will be used as inputs to the model has previously worked on a spreadsheet such as Excel. I would also recommend it to analyze problems of medium and small size. Given the experience I have had when I have used it with large problems, there have been noticeable decreases in the speed of response (which are not associated with the size of the system of equations involved in the calculation). Excellent for processing linear programming models.
Information Server is extremely useful to replace manual developments that require a lot of coding effort. It significantly increases the productivity of the initial development and the future maintenance of the processes since it has a visual development environment with self-documentation.
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.
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.
- 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.