In a perfect world, analytics infrastructure should change together with businesses requirements. So, as business challenges evolve, so too should the technology that provides the analytics critical to business success. Unfortunately, organizations that rely on standard SAS software (and some may have been hooked as far back as 1972) must deal with exorbitant prices, vendor lock-in, and constrained scalability. The answer?
New developments in open-source, zero-code SaaS platforms like UBIX mean that SAS modernization projects can be tackled with a data intelligence cloud that reduces dependencies on proprietary systems and the costs of dedicated tools and resources. So, the good news is that you won’t have to wait months or even years to realize the benefits of an intelligent cloud for your SAS modernization initiative.
Why should you consider SAS modernization now?
The short answer to this question is that a typical reduction in total cost of owner (TCO) over three years will approximate $37.5M which translates to an 88% reduction. In the attached chart, which provides an illustrative use case, you can see that current state SAS requires an annual license fee of $10M which sets up a minimum $30M 3-year TCO. The recommended transition to SAS Viya will actually increase TCO and continue to lock you into proprietary architectures with a 3-year TCO of $42.5M. The good news is that modernizing with a Data Intelligence Cloud for AI will generate a 3-year TCO of $5M which provides that 88% reduction identified above.
These savings are realized by:
- Eliminating Licensing Fees: Retire costly SAS licenses by migrating to Kyndryl no-code visual workflows that encapsulate Python code.
- Reducing Infrastructure Costs: Shift from fixed, on-prem SAS environments to UBIX’s cloud-native platform with usage-based scaling.
- Lowering Maintenance Overhead: Simplify operations with automated provisioning, no-code interfaces, and fewer integration points.
- Smarter Workforce Investments: Empower broader teams with no-code tools based on open-source Python, reducing the need for specialized SAS expertise while fostering collaboration across technical and business users.
You can also realize the following benefits
- Greater Flexibility & Innovation: UBIX enables modern AI/ML workflows with cloud-native architecture, open-source integration, and no-code tools—supporting faster experimentation, automation, and continuous improvement.
- Broader Talent Accessibility & Collaboration: Python code can be encapsulated in KDIC’s no-code interface, enabling collaboration between developers and business users while reducing reliance on SAS-specific skills.
- Significant Cost Savings: Eliminate high SAS licensing and maintenance fees while optimizing compute resources with UBIX’s scalable, usage-based infrastructure.
- Vendor Independence: Move away from proprietary platforms toward open, modular architectures that adapt more easily to future technologies and evolving regulatory requirements.
- Rapid Innovation: With automated provisioning, integrated pipelines, and parallel innovation during migration, UBIX delivers business insights in days—not months.
How to mitigate risk during the transition
One of the most common objections to attempting a SAS modernization project is the potential disruption to current business operations. This can be minimized by following this recommended approach:
- Phase the Rollout: Begins with automated inventory of all SAS workloads to identify priorities and reduce risk.
- Establish a Dual Environment Approach: SAS runs in parallel with UBIX to ensure continuity and smooth validation.
- Deploy Workload Evaluation & Migration: Workloads are assessed and categorized; high-value code is refactored and migrated to Python in UBIX’s no-code ModelSpace, while redundant workloads are retired.
- Leverage Pre-Provisioned Infrastructure: Key data sources are connected early to support analytics and AI from the start.
Deliver value in days or even minutes instead of months or years
Vendors like UBIX deliver on the promise of a zero-code, highly scalable and flexible cloud architecture that leverages the best-in-class cloud technologies to support modern data workloads, including analytics, AI, and ML. A perfect fit for any AI transformation or intelligent cloud project. With an architecture that is designed to adapt to the varying demands of large financial services enterprises, allowing them to scale up or down based on their specific requirements. In doing so you will realize long-term value creation with:
- Faster Insights & Decision-Making: Enable real-time analytics powered by cloud and AI.
- Agility & Competitive Edge: Future-proof your data ecosystem to adapt to evolving business needs.
- Enhanced Security & Compliance: Cloud-native platforms provide enterprise-grade security and regulatory compliance.
- Seamless Data Integration: Connect effortlessly with modern BI tools, data lakes, and machine learning platforms.
- Scalable & Cost-Efficient Architecture: Pay for what you use, and scale analytics workloads as needed.
- Lower Total Cost of Ownership (TCO): Achieve significant savings within 3–5 years.
How can you get there?
Start by learning how GenAI and emerging advancements like Reinforcement Learning can deliver on the promise of a data intelligence cloud for life sciences industry analytics has never been easier. Download our free eBook titled “Solving the Problem of Data and Decision Making” to help better understand the nuances of emerging AI concepts and technologies and offer a set of best practices for consideration to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AI Readiness Workshop, you can contact one of our AI experts today.