Claris FileMaker vs. IBM SPSS Statistics vs. SAS Viya

If your company is really small, I can understand the need for a product like this. However, I would go for MS Access... FileMaker Pro can not be integrated with other systems (like MS Access can at least be handled by C# for instance, and can be integrated with MS Excel or even SQL server). I'm really not sure in what scenario one would choose for FileMaker Pro. If your application or company grows bigger, you're going to have a problem to move to another environment. Also, the fact that only one person can work with the backend at any given time is a problem in a somewhat larger company.

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IBM SPSS Statistics is well suited for pretty much any data analytic scenario. It can handle extremely complex and large-scale datasets with ease. It especially shines if you have to do any kind of analyses that involve significance testing. Being able to do any number of significance tests (i.e., t-tests, chi-square, ANOVAs, etc.) right inside the tool is very valuable. The only scenario I would say it is less appropriate is if you need to work on a very small dataset and answer very simple questions, like frequencies or averages. In those cases, something like Excel could probably do the job just as easily.

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SAS Advance Analytics is well suited for data that is visual. Data where you want to see multiple graphs and models are good for this software. However, if your data is more descriptive this may not be the best program. SAS is well suited for data where you need to make comparisons on the feasibility of two different programs. Data that can be compared is perfect for this software.

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• The relational database management system makes the program highly customizable to fit the needs of any product. You can add a ton of information to each record and update your inventory on a regular basis with an Excel import or manually inside of the record. It has the capability to incorporate barcoding, which can manage your available inventory with ease.
• The scripting language allows FileMaker to automatically calculate complex algorithms automatically or generate report outs with the click of a button. This allows for greater UI, especially with active users who are not familiar with writing code. Almost all of our internal data is linked to the FileMaker database
• The server license allows many users to update the database in real time, which is handy if your inventory is constantly changing. We have users with Macs, PCs, iPhones and handheld tablets linked to our FileMaker database and they are updating the information constantly throughout the day.
• If you invest some time into formatting and scripting the database, there is a high ease of use for users without knowledge of any programming or FileMaker itself.

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• SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
• Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
• SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
• SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
• In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.

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• SAS is can be used as query builder tool which can automate a lot of excel process.
• There are variety of statistical options available that tie up good visual analytics.
• There are inbuilt models available for different operations which doesn't require any coding and are easy to run.

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• Developer features need to be beefed up - namely adding the ability to search code for a phrase or keyword and the ability to do the same in the "relationship graph" in the database.
• Add ability for users to edit the same table record at the same time by version control.
• Allow Filemaker Server to use more than 1 core; currently multi-processing is not supported and it can be tricky to find just the right server to support the application you've built to the fullest capacity.

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• Cost is becoming prohibitive.
• Availability of procedures in the base package seems to be dwindling.
• The copy-and-paste function from output to Excel is not as easy as it once was (now I have to do a "paste special").
• Text and date handling are terrible.
• Need to include AI-based NLP for survey verbatims and other text-based fields. This is becoming increasingly important in the CX world, yet SPSS seems to be ignoring it.

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• SAS Analytics does not have very good graphic capabilities. Their advanced graphics packages are expensive, and still not very appealing or intuitive to customize.
• SAS Analytics is not as up-to-date when it comes to advanced analytical techniques as R or other open-source analytics packages.

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It it not really up to me but my opinion does have some weight in the decision and the reason I would renew my use FileMaker Pro 8.5 is because I am finally getting used to it! Now that I have been working with the program, tasks have become quicker and projects are getting done faster. File Maker Pro 8.5 really is a versatile tool and I think we are just scratching the surface with it's abilities.

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Both
money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis
using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data
entry and data analysis for my research. Output from SPSS is very easy to
interpret for data analysis and findings

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Not only does SAS become easier to use as the user gets more familiar with its capabilities, but the customer service is excellent. Any issues with SAS and their technical team is either contacting the user via email, chat, text, WebEx, or phone. They have power users that have years of experience with SAS there to help with any issue.

It's almost what it should be after so may years and with Apple's longevity and strength behind it. For people who earn their living based on efficiency I think there are too many developer obstacles that waste time and therefore money.

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Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.

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If SAS Enterprise Guide is utilized any beginning user will be able to shorten the learning curve. This is allow the user a plethora of basic capabilities until they can utilize coding to expand their needs in manipulating and presenting data. SAS is also dedicated to expanding this environment so it is ever growing.

mostly never issues and if there are they are resolved fast

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SPSS can tend to crash when I am trying to do a lot of data. This can slow me down when I need to do a lot of data

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SAS probably has the most market saturation out of all of the analytics software worldwide. They are in every industry and they are knowledgable about every industry. They are always available to take questions, solve issues, and discuss a company's needs. A company that buys SAS software has a dedicated representative that is there for all of their needs.

for the most part but lots of error messages if you type something h correctly

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SPSS does the job, but it can be slow. I do have to plan a lot of time to get through a huge amount of data.

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Although nothing is perfect, SAS is almost there. The software can handle billions of rows of data without a glitch and runs at a quick pace regardless of what the user wants to perform. SAS products are made to handle data so performance is of their utmost important. The software is created to run things as efficiently as SAS software can to maximize performance.

The forums are great with lots of helpful experts and the staff monitor them to provide help where needed. There have been a couple of unique technical issues I've had to deal with that I haven't been able to get resolved so I chose to score this a 9 instead of a 10.

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I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end

SAS is generally known for good support that's one of the main reasons to justify the cost of having SAS licenses within our organization is knowing that customer support is just a quick phone call away. I've usually had good experiences with the SAS customer support team it's one of the ways in which the company stands out in my view.

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easy to follow along and was able to jump in right away

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SAS has regional and national conferences that are dedicated to expanding users' knowledge of the software and showing them what changes and additions they are making to the software. There are user groups in most of the major cities that also provide multi-day seminars that focus on specific topics for education. If online training isn't the best way for the user, there is ample in-person training available.

There are online videos, live classes, and resource material which makes training very easy to access. However, nothing is circumstantial so applying your training can get tricky if the user is performing complex tasks. When purchasing software, SAS will also allocate education credits so the user(s) can access classes and material online to help expand their knowledge.

Suggest you use an iterative R.A.D. or AGILE development approach. (i.e. rather than writing a gigantic spec for a system, then building it). FileMaker facilitates quick prototypes. Developing an example, then allowing users to "try it out" is a snap.

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Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.

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Ask as many questions you can before the install to understand the process. Since a third party does the installation your company is sort of a passanger and it is easy to get lost in the process. It also helps to have all users and IT support involved in the install to help increase the knowledge as to how SAS runs and what it needs to perform correctly.

FileMaker is still the quickest way to go from zero to having a minimum viable working solution. Simple solutions can be built in as little as a afternoon of development. It is the only tool I am aware of which allows tech savy end users with domain knowledge to build bespoke apps for their businesses without undertaking professional software development training.

If you have made it this far, you should have a very good idea of how SPSS stacks up the competition (data processing and analytics tools). Even the free ones, such as r Studio or Stata, are leaps and bounds ahead of SPSS. IBM is resting on a reputation developed nearly 30 years ago and has shown no desire to improve.

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SAS was the incumbent tool, and what the team knew. We did look into using Revolution Analytics enterprise version of R, but the learning curve on that caused us to stick with SAS. In my current position, I've opted for WPS over SAS. I can still leverage my SAS experience, but the price is about 15% of what SAS charges, with extra functionality, such as direct database access. I can supplement WPS with free software, such R for anything that it might be missing.

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it's most definitely does as we are a unique business to use this for scholarship awarding

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I am neutral because I have not had to look into scalability since I am using as a student.

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It all depends on the type of SAS product the user has. Scaleability differs from product to product, and if the user has SAS Office Analytics the scaleability is quite robust. This software will satisfy the majority of the company's analytic needs for years to come. In addition, if SAS is not meeting the users needs the company can easily find SAS solutions that will.

• We are a more agile company because of FileMaker. A few of us who are tech-savvy enough to manage the database (but are not professional developers) can make needed adjustments to our database without having to employ an in-house developer or contract with a 3rd party. As our business processes evolve and change, it's easy to update the database to accommodate those changes.

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• I found SPSS easier to use than SAS as it's more intuitive to me.
• The learning curve to use SPSS is less compared to SAS.
• I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.

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• SAS is pretty expensive, so a company would need to take that into consideration before purchasing a license.
• A lot of companies are now starting to use SAS Advance Analytics, it is great for sharing data between departments.
• Presentations come out better when using SAS, and estimates are more precise to the confidence interval.

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