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By Patrick Nussbaumer, Director of Product Marketing, Domino on June 17, 2021 in Perspective
As a data science practitioner, you are acutely aware of how machine learning models can fuel business success.
Models can help your company beat the grueling war with competitors.
Models can help guide leaders through strenuous change for growth.
Models can topple mighty competitors who ignore this resource.
Domino is all about using machine learning models as a business weapon. We believe organizations that put models at the heart of their business via an Enterprise MLOps platform will beat competitors, drive unprecedented growth, and upend industry giants. These will be “model-driven” businesses, and they will win.
If your organization is somehow on the fence about whether you should invest in an Enterprise MLOps platform, we present a short guide of the five reasons why you should not buy the Domino Enterprise MLOps solution. Whilst the guide is satire, the query is serious: Is an Enterprise MLOps platform right for you?’
1. You Believe Unlimited Tools and Compute are Overrated
Maybe your data scientists never need more than a basic laptop, and you can’t understand why anyone would need distributed computing, GPUs, or other modern infrastructure.
Is your IT team just waiting for you to ask for help, willing to jump on your requests in minutes?
In your world, do your data scientists just smile and use whatever tools they are told to use?
If you’re like most data science leaders we talk to, access to data science tools and infrastructure is a big pain point.
Domino makes it easy to use whatever the task needs.
The Domino Enterprise MLOps platform is a portal to power. Virtually any data science tool and infrastructure at enterprise scale. Easily provisioned. Instantly available.
There’s no lock-in or waiting on busy IT staffers to provision resources. A recent Forrester Consulting study found that Domino saves an average of 70 hours to spin up a project’s resources! Domino lets you leverage the best tools for your business problems.
2. You Love the Movie “Groundhog Day”
If you’re leery about trusting a model that someone else created, do you just build a new one?
Maybe data scientists never leave your organization. If that’s the case, congratulations! It’s handy knowing that your entire team has been intact since the beginning of time, knows where everything is, and has knowledge of every project ever completed.
Or, perhaps you believe that the best way to weed out bad data scientists during onboarding is with repetitive projects?
The reality we hear from data science leaders is that their teams are always “reinventing the wheel.” Reproducing the work of past team members is difficult and results in key-person risk.
Domino lets you reproduce any research.
Get Domino and you’ll enjoy a searchable system of record tracking all related artifacts for any project at the experiment level. You can reproduce, and reuse, to focus on more valuable insights.
3. You’re Convinced Silos Keep Data Scientists Focused
Maybe your company deliberately silos data scientists.
Are your data scientists happiest at incubating ideas in isolation?
Do data scientists prefer the glory of being an independent genius who discovered the next breakthrough?
Most data science leaders we meet are looking for ways to break down silos and accelerate collaboration.
Domino enables a culture of collaboration.
With a single pane of glass, the Domino platform lets data scientists collaborate independently of tools so teams can focus on solving more complex problems. Put your teams on Domino for a continuous learning loop that drives an ever-growing flow of business value at scale.
4. You See Shadow IT as a Team Sport
Perhaps you’re fortunate to work for an organization without IT policies that restrict data scientists from downloading and using whatever tools they want? Is “possession” the name of the game?
Do your data scientists embrace the entrepreneurial spirit when they are free to work outside of corporate boundaries?
Maybe the server under your desk lets you get models into production without bureaucratic steps of validation. And it keeps those feet warm during the winter.
The organizations that scale data science effectively are those that figure out how to satisfy corporate requirements for security, risk, and compliance without sacrificing data science productivity.
Domino easily supports everything you prefer at enterprise scale.
No more shadow IT! Give your data science teams Domino so they can use their preferred tools, packages, and infrastructure. IT can slash support costs while improving security, governance, compliance, collaboration, and reproducibility.
5. You Can’t Increase the Productivity of Ph.Ds
In your world, do you pay your data scientists on a per-model basis? Do you keep costs under control by limiting productivity?
Do you find that your data scientists enjoy performing manual tasks? I know, automation is a thing. But it’s like hand-building a Swiss watch. Automation is at odds with quality, right?
Is speed frowned upon in your organization? Is slow and steady the name of your data science bowling team?
Wait for it…
All too often, we see data science teams who are spending too little time on research, as they need to perform all sorts of related tasks to make progress.
Domino enables high-velocity creation and deployment of models.
With Domino, model friction is gone. Our Enterprise MLOps platform provides a common way of working, with workflows that accelerate the lifecycle of each step and across key transitions. No matter what tools are used, Domino lets data scientists accelerate time to value – something we call “model velocity.” But don’t take my word for it. Check out the recent Forrester Consulting study I mentioned, The Total Economic Impact™ Of The Domino Enterprise MLOps Platform. Forrester found Domino delivers faster model validation averaging 20 hours per model. And a three-year total return on investment of 542 percent!
Sometimes absurd ideas are the ones that trigger common sense. If good enough is not good enough for you, I invite you to check out Domino today. I have a hunch that Domino is something your company will want to buy!
And if, after reading this, you’re bold enough to build your own platform, we invite you to get a reality check on the topic. Check out, The True Cost of Building a Data Science Platform, before you take the plunge.