I have almost 10 years association with SAS technologies but I am very concerned to see the migration to R/Python/Pyspark/Altair etc. Is SAS doing any concrete work like increasing reach out to customers, considering decrease of prices of licenses, increasing flexibility to install packages as per user's will, improving performance /visualization features providing value add on services etc..?
I am very concerned with my career and the way that I observe that the way it is going, SAS engagements will enterprises will shrink more and it would be very disheartening for me to see that.
Are there any enterprises which have shifted to new technologies and have come back to set up SAS shop?
I would highly appreciate if I get replies from senior persons at SAS or within SAS community. The clarity would be required for motivation to chart the future path for me.
Personally I'm not losing any sleep over this issue. Rumours of SAS's demise started about the time it became available commercially and no doubt they will continue. Back in the day, IT professionals were saying SAS is going to be replaced by SPSS, Focus, APL, "name any other old 4GL". Guess what? SAS has outlasted all of them.
The problem with all of those other products that you mentioned is that their greatest strength is they are open source. That's also their greatest weakness. Where do you go to get gold standard technical support, gold standard upward version compatibility, gold standard scalability, and gold standard maintenance with open source? Organisations recognise this so they don't use open source software for business-critical applications - one of SAS's strengths. Open source can co-exist alongside SAS to provide great modelling and analytics capabilities, but it isn't a good choice for business-critical applications.
@AnirbanJD1 - SAS is in the middle of re-architecting their technology to be more up-to-date and cloud ready - SAS Viya - as well as launching new business applications. Check out the Viya product pages if you want to find out more. I think that proves SAS is not standing still and is continuing to evolve to meet market demand. Yes, the competition is heating up but where I am SAS still seems to be doing OK. Yes, there are customers moving away from SAS to other products, but SAS is also gaining new customers. That's business as usual.
Minor edit: this year's conference is SAS Innovate 2024, not SAS Explore. https://innovate.sas.com/event/8ab28f0a-ebf2-40d1-a8e7-650dc34d7777/summary
@AnirbanJD1 I would encourage you to look at the announcements that came out of SAS Explore 2023, and consider attending SAS Innovate 2024. I went last year, and it was great to learn more about the SAS roadmap. When you're there in person, you can hear the presentations from the main stage, and also have side conversations with developers and partners in the innovation hub. The side conversations are very valuable.
Big picture, I agree with @SASKiwi , it's clear that SAS is innovating. With cloud-native Viya, with continuing support for 9.4, and with new products like cloud-native Workbench (announced at SAS Explore 2023, I think of it like a personal SAS 9.4 instance running in the cloud, but it's much more than that). I'm also interested in the partnership between SAS and Snowflake. There were Snowkflake reps at SAS Explore, as well as Microsoft reps and other partners. I wonder if the market battle will be SAS+Snowflake vs Databricks.
That said, I don't mean to minimize your concerns, as I think they are very valid. The analytics marketplace is very different than it was 10 or 20 years ago, where SAS would have been the undisputed leader (IMHO). I'm basically a one-trick (SAS) pony myself, and it still feels risky to me, even 25+ years in. With regard to R and Python, SAS is embracing open-source integrations. As you say, given the diversity of products in the analytics marketplace, it definitely makes sense to me to develop experience using multiple products / languages / etc. I'm hoping to spend time in Databricks/PySpark this year.
If you want one more thing to worry about (I'm a worrier!), SAS is still planning to be ready for an IPO in 2025. So even if you understand the SAS roadmap now, there is potential for it to change after an IPO or acquisition.
@Quentin wrote:
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If you want one more thing to worry about (I'm a worrier!), SAS is still planning to be ready for an IPO in 2025. So even if you understand the SAS roadmap now, there is potential for it to change after an IPO or acquisition.
I was unaware of a planned SAS IPO (but now I have read SAS charts path to IPO-readiness). This to me is likely to be a far greater issue than the others mentioned so far. Publicly listed companies are far more likely to suffer from the tyranny of quarterly financial reports than privately held companies. True, this might give more apparent urgency to some of the concerns expressed by @AnirbanJD1, but it will also likely create more marketing effort to convince customers to upgrade to the latest offering as opposed to sustained support of older products. It also can result in a focus on specific (high ROI) niches at the expense of offering and improving a broad array of capabilities.
Of course, something like this has to happen. Jim Goodnight can't live forever.
Great post @Quentin ! I had heard about the IPO, but wasn't aware it had been pushed out to 2025. One of the most significant challenges SAS faces is that many teaching institutions now teach analytics with open source languages and one of the primary drivers for that is cost. What that means when these students move into the job market is that they favour these products when choosing analytics tools (a case of what you know) and it also means that existing SAS sites are finding it harder to recruit job applicants with SAS skills. My boss is always complaining about this problem. There are just many more job applicants with open source language skills than with SAS.
Hi @AnirbanJD1
If I may add to @Quentin , @SASKiwi responses. I would highly advice you to:
1. Learn how to integrate these technologies and use the best of their combinations where possible.
Both SAS 9.4 and SAS Viya provide integration with Python, R, Lua, and Java. Their level and method of integration do vary, but you do with what they offer.
2. Do not listen to the old line of "Open Source Software such as R & Python can not handle large data"!, Whoever repeat that line to you, knows nothing about the recent advancements in the OSS universe.
OSS is becoming the mainstream right now, and no one can stop its wave!
So you'll be better served riding it rather than ignoring it and getting subsided by it.
just my two cents,
Ahmed
Disclaimer for generalization, and my from the market me and my company operates...
I see groups/segments:
- Big DW/BI SAS shops. Heavily invested in SAS, will (hopefully) migrate to Viya when SAS Studio Engineer and migration tools are up to par with customers expectation.
- SAS solutions, like Risk, AML/Fraud etc. Once sold in, customers are very dependant of this functionality, especial when regulatory requirements are involved. Even if these are late to Viya, I see no acute threat of churn.
- Small/medium BI/reporting/analysis sites: here I'm seeing definitely a movement away from SAS. New initiatives on other platforms.
All and all, I can understand your worry.
As mentioned in the thread, SAS is raising support for Python/R workloads in Viya. Question is if it's enough and not too late...
Thanks to all for the participation. Unfortunately I cannot afford to visit the global forums like Innovate etc. hence would be dependent on announcements and articles about the proceedings in these events.
I was aware of the IPO readiness but under the impression that IPO would be launched in 2024. Now if it has been pushed to 2025, then that is quite disappointing for me I must say.
Getting the academic students having a lot more exposure to SAS is the need of the hour, and if the backlogs in this category are not addressed then the future students might not be knowing/just be having a bare idea about SAS in their academic years . Surely the Open source softwares have come a long way and I had been seeing the use of Open source Analytics in Life sciences and Banking & Financial services which were supposed to be bastions of SAS. Add to that the the very impactful influence of Cloud providers and technologies like Databricks , Google BigQuery adding to the pain of SAS. The footprint of SAS is not observed that much in the promising domain of Data management(including Data integration, Data catalog etc.)
The AML, Fraud softwares provided from SAS appear to be good but these are niche areas and the SAS ecosystem cannot be dependent on few niche areas.
Now that the problems of the SAS ecosystem are clear and evident and also facing falling market share can the following points be addressed?
I really hope that the decision makers of SAS ecosystem take a look at this post and do the needful things very swiftly
a) Increase the exposure of SAS to Academic students to a great level including sponsoring events, hackathons etc events and organizing other learning events
b) The IPO should be made ready at the earliest possible and the license/new procurement costs need to be decreased by a drastic amount
c) Improving the features of the SAS technologies and applications wherever applicable to make it a very attractive option for the Decision makers at the Business side.
d) get involved in Open source more, create utilities /sub-softwares etc. to have a broad reach. A notable issue with the SAS ecosystem is that there are not any mechanisms to import packages and run . Can this be introduced with creation of Multiple SAS packages( for the various algorithms and techniques) and providing the flexibility to the users to import the packages from SAS repository, install and run codes/workflows?
e) Improve /build applications for the data management domain to make SAS offerings an attractive option for the Decision makers of the Business.
f) Other Business domains like retail, telecom etc. need to be thoroughly explored with an aim of increasing the the relevance and acceptance of SAS.
g) Identify other new growth areas like geospatial analytics, creating query languages of SAS for geospatial analysis, finding use cases in cybersecurity domain, and if law allows, then aggressively work on GenAI, LLM domain.
h) Identify how SAS can be used in areas of Quantum machine learning, Quantum finance.
I am a very long term user and proponent of SAS ecosystem and it is very disturbing for me to see that SAS ecosystem getting side-lined gradually. Even though I have increased my expertise in Open source and Cloud technologies, but I would always prefer to have SAS as my primary skillset in short as well as long run of my career. Hence I would be very grateful and satisfied if the needful actions are taken by the stakeholders and bring SAS softwares and technologies regain position under the limelight.
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