Alteryx Platform vs. Anaplan vs. IBM SPSS Statistics

I would 100% recommend Alteryx to a friend, for me its friendly interface is the best, it has all the tools I need without the headache that programming is. It can be used for simple or complex analysis, so honestly, I don’t see a scenario where it wouldn’t suit. I’ve used Alteryx to make simple things I could do in Excel, for example, but it was less complex and faster to do in Alteryx, so why not? Its a very versatile tool.

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With its versions and native time features Anaplan is well suited for all activities around planning in time and scenarios. Tasks involving calculating across multiple dimensions make Anaplan shine - the easiness to build complex calculation and present results on customizable pages. With its access restrictions it's well suited also for working with sensitive data (employee and customers personal data).

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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• Pulling data from multiple disparate data sources.
• Allows users to see the data at every step of the workflow to be able to cleanse, analyze, and optimize the data.
• Provides an analytics platform that is easy for users of all levels to thrive in whether they are just starting out in their analytics journey or they have a master's degree in Data Science.

• Anaplan removes the time consuming process of integrating the results of individual spreadsheets.
• Anaplan facilitates the standardization of assumptions across all sub-processes
• Anaplan provides full transparency of the calculations and source inputs
• Anaplan allows us to automate certain planning processes that would have been impossible when relying on the computational capabilities of an individual computer.

• 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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• Steeper Learning Curve: Alteryx can have a steep learning curve for users who are new to the platform or have limited experience with data analytics. Enhancements to the user interface and user onboarding resources could help make the learning process more intuitive and accessible to a wider range of users.
• Enhanced Data Visualization Capabilities: Alteryx offers basic data visualization capabilities, but there is room for improvement in terms of advanced visualizations and interactive dashboarding features. Adding more sophisticated chart types, interactive widgets, and customization options would enhance the data visualization capabilities within the platform.
• Improved Error Handling and Debugging: Alteryx provides error handling mechanisms, but enhancing the error reporting and debugging capabilities would be beneficial. Improved error messages, better visibility into data flow, and debugging tools could help users troubleshoot and resolve issues more efficiently.

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• Some end users don't spend the required amount of time to familiar themselves with Anaplan.
• Auditability, while good in theory, can be lacking and clunky when needed.
• Model building can become convoluted over time, leading to confusion over the specific use of line items.

• 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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We've developed a working partnership with Alteryx. As an enablement suite, we're continuing to innovate and deliver great products with use of Alteryx in our solutions. Alteryx use expands to our global product development teams and is in use in multiple parts of our organization. Alteryx also delivers Experian demographic content to other clients in their product offering. We're highly likely to renew, but that decision is way above my pay grade.

Anaplan is a very strong multi-dimensional modeling tool that provides a calculation engine to empower a complex planning process. It is fairly easy to learn for those with experience in similar tools, or excel. It forces structure and auditability that spread sheets do not have, along with extensive security capabilities

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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I've found that while some things might take a little longer to create, the flexibility of Alteryx allows you to perform any function needed. I haven't found a use that was not available in Alteryx yet. APIs and XMLs can be created to perform certain functions. In addition, CMD line commands can be sent using Alteryx to perform certain functions as well.

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Anaplan's usability is dependent on who is implementing the project and how clear business processes are at the beginning of the implementation. Complex business processes with many inputs and reviews will still be complicated in Anaplan; however, the UX is very flexible in how to help people through the process and there are also other items such as Workflow that can help people move through the system.

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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I use many programs and compared to others, Alteryx virtually never goes down, freezes up or gives an application error. Over a 4 year time period that I have used this program, any of these may have happened 3 times. It is an incredibly stable program that I feel completely confident in.

There are very few outages. Maintenance is scheduled on two or three Saturdays per month, so as not to affect businesses. When there is an outage, users are kept informed of progress to restore the platform and typically this takes no more than an hour. Anaplan customer support is very responsive if we ever have questions about platform issues

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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I already gave the example of journal entries created in less than a second. What else can I tell you about.... I can tell you those 2 journal entries have historically had to be split into separate accounting systems so the outputs had to be very different (D365 vs Intacct) such that they are exactly ready for uploading. I can tell you I used to have some tire and battery queries hitting a line item detail table and they took hours to run UNTIL I asked IT for a view in SQL and now they're ready in about 5 minutes total. I guess I'd say if anything does take a long time - do some research with others and figure out what would speed them up

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Everything is calculated in memory in the cloud. It's nearly instantaneous updates when you make changes. The only time things get a little slow is when you have a massive model with very intricate calculations...but "slow" for Anaplan is not what I would call "slow" for something like Hyperion. We used to have Hyperion calcs that ran for 60 mins before you could use data. The equivalent would be 60 seconds in Anaplan.

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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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Stellar, bar-none. Some of the best support folks of any vendor. The Alteryx Community is the most responsive and supportive. On the rare occasion of a release issue or bug, we've been able to get quick help to solve the core problem. Alteryx does not play the blame game. They genuinely help the users solve their issues or respond to questions

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Support quality has dropped since Thoma Bravo has taken over. I think some serious re-focus needs to happen here -- part of the beauty of being in the Anaplan community was how involved you felt in it before. Before I didn't dread sending a support ticket, now I am starting to.

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

1st level of trainings which I've attended in Paris was easy and I was already knowing %90, that learning could have been an e-learning instead of in-person

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In my opinion, in-person training is always the best if you have the option to do so. This allows real-time interactions with the instructions, whereas the online training I took required me to write-down questions, email them, and wait for responses. This slows down the process, as you can imagine. That said, in-person training is an extra cost and it likely isn't needed for everyone. I would suggest selecting a small number of people to take in-person training and then having them act as mentors to the rest of your team. That way, as the rest of the team takes the online training, they have a resource to help them in real time.

Very good, detailed online trainings which you can take at your own pace, and strong certifications exists, certifications are extremely detailed and hard...

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Anaplan training materials are clear, simple, easy to understand and to follow. Visuals are excellent. The vendor is good at updating training materials in a timely manner and encouraging users and administrators to keep coming back to Academy site for refresher courses or new feature courses. I really like their interactive diagrams

There is really not much to it (the installation, that is). Once you get it installed, along with any of the add-ons (demographics, R, etc.), you are up and running almost immediately. There is really no additional setup. You can immediately begin blending data, running demographics, performing spatial queries, running predictive analysis, etc. And for many of these functions, the learning curve is quite easy.

One key insight from implementing Anaplan is that success comes from focusing on designing the process, not just building the model. Anaplan is extremely flexible—there are very few planning scenarios it cannot support—but that flexibility means the project needs strong governance, clear ownership of requirements, and a well-defined data model. When those foundations are in place, implementations are fast, iterations are easy, and users can quickly see value.
In our projects, both Financial Planning and Integrated Business Planning models were adopted smoothly because we involved business users early, kept the model design intuitive, and leveraged Anaplan’s Excel-like syntax and user-friendly dashboards. The result was more efficient day-to-day work, reduced manual tasks, and increased collaboration across teams. In short: when you combine Anaplan’s flexibility with a structured implementation approach, adoption and value realization happen quickly.

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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Alteryx is MUCH more user friendly. both provide the ability to code within them, but Alteryx has much nicer interface. The formula tools have a more simple language that is easier to learn than formulae in SSIS. Alteryx is easy to read with multi colored tools identifying what each one does. It also allows for macros. You can build your own tool to process records of data or batch records together.

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Anaplan is more powerful than Pigment considering that it is an Enterprise class system and is able to manage bigger data sets. Anaplan allows for advanced scenario modeling and formula capabilities along with custom reporting functionalities. Anaplan has proven its capabilities and stability across various use cases and across bigger enterprises when compared to Pigment which is still in earlier phases of its development

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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Individual analysts can quickly generate results using their own copy of Alteryx Designer. But using the Server and developing macros for more complex needs can be time consuming.

We have managed to leverage Anaplan for financial planning and forecasting across the business. It is now used by almost every department, with more than 50 users (but I know of companies that have hundreds of users) and still the platform is quick and reliable. It is easy to make changes to divisions and departments or add users and apply different user settings - the core part of the model is not affected and end users can continue their work without any disruption

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

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• Error handling - allows controls to be built into workflows easily and allows them to be isolated and spat into control reports that can be easily reviewed and audited, thanks to the ability to create multiple outputs in one go.
• Time-saving - saved huge amounts of time, especially when moving Excel processes into Alteryx.
• Product development - allowed my firm to create products that we have been able to market and sell to clients.

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• Anaplan's implementation led to a significant reduction in planning cycle errors and bugs, streamlining processes and improving overall accuracy in data inputs
• Standardizing the planning process and enabling cross-functional collaboration through Anaplan enhanced our ability to adapt swiftly to changing business needs, resulting in improved agility in decision-making
• The platform's capabilities, especially in Demand Planning and Supply Chain, positively impacted our ROI by optimizing resource allocation and solving complex business problems efficiently across multiple functions

• 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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