The search to maximise our personal productiveness is endless. All of us wish to be extra environment friendly in our work and carve out extra time with family members.
As you assess knowledge and AI expertise to automate processes and maximize effectivity, you could surprise if it’s really potential for you or your group to undertake a knowledge and AI platform and make enormous beneficial properties in human productiveness, whereas additionally curbing prices and constructing belief in outputs.
The reply is sure. It’s potential.
The short take
We engaged a third-party analysis agency, The Futurum Group, to conduct efficiency and productiveness research on our knowledge and AI platform.
The primary examine evaluated the efficiency of AI coaching fashions.
Carried out over 1,500 exams throughout varied datasets.
Used the identical compute assets for all exams.
Findings: SAS® Viya® is 30 instances sooner than alternate options and 49 instances sooner than a industrial Spark-based platform.
The second examine evaluated the productiveness of individuals finishing knowledge and AI duties engaged on a real-life end result.
Findings: SAS Viya allows important productiveness beneficial properties for knowledge engineers, knowledge scientists, MLOps and enterprise analysts.
As properly, low-code/no-code capabilities and productiveness for non-technical customers within the knowledge and AI life cycle provide enormous beneficial properties. It is a huge win for fixing the expertise hole.
“Testing confirmed that an end-to-end knowledge and AI lifecycle will be achieved with greater than 4 instances larger productiveness in SAS Viya than in aggressive options,” mentioned Russ Fellows, VP and analyst at The Futurum Group. “The power to rapidly start working, along with SAS Viya’s productiveness allows AI groups to quickly produce enterprise outcomes and insights from their knowledge.”
So, how did we do it? Listed below are six fast suggestions for maximizing human productiveness whereas decreasing prices and bettering knowledge and AI outputs.
Tip 1: Finetune knowledge entry and prep
Allow groups to find knowledge, analyze it and construct a list with high-quality knowledge that’s correct, full, constant and well timed. This knowledge have to be trusted to make essential enterprise selections. Poor-quality knowledge with out correct knowledge processing can result in misguided methods and dear errors. The platform should assist strong processes for dealing with knowledge all through its life cycle – from acquisition and integration to cleaning, governance, storage and preparation for evaluation.
The Futurum Group discovered knowledge engineering duties, like knowledge administration, on SAS Viya had been:
16 instances extra productive versus the industrial platform different.
16 instances extra productive versus the non-commercial platform different.
Tip 2: Have a plan for AI ethics and governance
Knowledge privateness, knowledge sensitivities and compliance points are always-on concerns – we should know the accuracy of the info entering into, really feel assured it’s free from bias and guarantee selections based mostly on fashions are explainable. In different phrases, your technique must be constructed on belief. Use a platform that robotically appears to be like for and flags knowledge akin to age, race and gender. Embed knowledge high quality checks so you can also make knowledge privateness selections like masking values inside the knowledge.
A knowledge and AI platform ought to assist transparency to gauge mannequin accuracy and equity. SAS Viya gives a characteristic referred to as “mannequin playing cards” the place you readily see the at-a-glance well being of a mannequin – its supposed use with essential elements to know if a mannequin is a viable candidate for deployment.
Tip 3: Resolve the expertise hole
Expertise gaps exist in every single place and at a number of ranges, significantly within the scope and nuance of extra technical roles. Think about a corporation the place a wide range of people and groups, each technical and non-technical, are all empowered to execute duties like harvesting and analyzing knowledge, and even constructing analytical fashions.
Why drive your knowledge and AI setting to at all times require coding, limiting the productiveness of numerous groups? The Futurum examine confirmed that non-technical customers can full 86 % of knowledge life cycle duties utilizing SAS Viya, in comparison with 56 % within the comparative industrial setting and 47 % within the non-commercial setting.
Tip 4: Curb cloud prices
Within the cloud, time is cash. Staff effectivity isn’t simply necessary, it’s necessary.
“With Viya, you acquire a aggressive benefit,” mentioned Jay Upchurch, Govt Vice President and CIO at SAS. “As a result of your AI runs sooner and extra effectively on Viya, your groups study sooner and are extra productive, so that you see outcomes sooner. Viya provides you agility and resiliency that empowers your group to see alternatives earlier than your rivals do, whether or not these alternatives contain approving prospects for automobile loans, retaining trains secure or distributing merchandise from a retail distribution heart.”
The Futurum Group findings assist Viya’s efficiency with coaching AI fashions can decrease your value by greater than 86 % in comparison with alternate options.
Tip 5: Construct a life cycle for steady enchancment
The world is at all times altering, and which means your knowledge evolves, enterprise aims shift and fashions decay. Hold iterating and evaluating your fashions in manufacturing – monitor their efficiency, examine in on knowledge high quality, and retrain/tune them frequently. With a knowledge and AI life cycle administration system in place, your groups can rapidly iterate and study so the very best fashions are in manufacturing. SAS Viya helps this.
Tip 6: Prep for revolutionary expertise on the horizon
Be versatile and open to generative AI capabilities and instruments, significantly ones which might be simply accessible or naturally built-in into your present setting and present workflows. Perceive that you simply aren’t hamstrung by a scarcity of knowledge or technical expertise. Improvements like artificial knowledge and pre-built fashions are taking heart stage with broad applicability.
In accordance with Forbes, artificially generated datasets will change into the popular coaching floor for machine studying fashions. SAS just lately acquired the principal software program property of Hazy, a pioneer in artificial knowledge expertise, to equip prospects with essential and well timed artificial knowledge era capabilities.
Kathy Lange, Analysis Director, AI Software program at IDC, shared, “Artificial knowledge is a game-changer for corporations implementing AI options, particularly in sectors with strict privateness rules like well being care and finance. SAS’ acquisition highlights the rising requirement for artificial knowledge as an integral part of a contemporary AI toolkit, addressing knowledge shortage and privateness points, and bettering mannequin accuracy whereas lowering biases.”
Outcomes that matter in scaling human productiveness
Hear Bryan Harris, Chief Expertise Officer at SAS, share the outcomes from The Futurum Group.
See SAS Viya in motion
Watch Jared Peterson, Sr. Vice President, Platform Engineering, demo our end-to-end knowledge and AI platform.
