Rocketing Confidence in Data Science, Poll Finds: Are Better Tools the Reason?
By Lisa Stapleton2022-07-134 min read
Businesses are increasingly betting big on data science for ambitious near-term growth, just one more indication that the rapidly rising profession is making itself a huge force for innovation in fields as diverse as healthcare & pharma, defense, insurance, and financial services. Nearly half of respondents in a recent poll said that their company’s leadership expects data science efforts to produce double-digit revenue growth. A similar survey in 2021 put that same figure at only 25%, indicating growing expectations for the young profession.
That’s just one of the findings of Domino Data Lab’s recent Revelate survey that drew 151 responses from people associated with the field. Nearly 4 in 5 respondents (79%) said that data science, ML, and AI are critical to the overall future growth of their company. A full 36% called these technologies the “single most critical factor” in their company’s expansion.
What Businesses Need to Do to Reap Big Expected Gains
Where should companies focus their efforts to achieve such outsized returns? What would be most effective in helping the emerging discipline to fully make good on its huge potential? The survey’s findings illuminated these issues as well, finding that:
- The hardest technological issues related to scaling and operationalizing data science were accessing appropriate data science methods/tools (27% of respondents say that’s their most significant challenge) and security considerations (26%).
- The largest people-and-processes challenge is still having enough data science talent, according to 44% of respondents, in keeping with many other recent surveys. Savvy business leaders should therefore make every effort to use their existing data science teams as efficiently and effectively as possible.
- The improvements that could best help data science step up its game include a tie: increased collaboration and on-demand access to data science tools and infrastructure, both at 43%.
Data science leaders also highlight the need for Enterprise MLOps platforms to help them solve the world's biggest challenges. In particular, many of them say they are optimistic because Enterprise MLOps tools are up to the challenge.
For example, Google’s chief data scientist Cassie Kozyrkov recently acknowledged the huge increasing confidence placed on the young profession. But as data science has become increasingly valued, companies such as Domino Data Lab are investing in creating and upgrading tools to support the young profession. Kozyrkov says the increase in the capabilities of tools, which are now being designed specifically for work in data science, is a very positive step in helping practitioners and data science leaders keep up.
“For example, Domino Data Lab has made tools for data scientists that are incredible, quite usable, and really lovable,” she says. “That’s what advocacy for our data science community looks like."
The survey was taken in May by attendees of Rev 3, a popular conference produced by Domino Data Lab for data science and IT leaders, as well as their teams. The conference, where Kozyrkov spoke, focused on the application of data science to some of the world’s most important challenges, and garnered more than 800 attendees in May.
Lisa Stapleton is a technology writer and editor in San Jose, CA. She has written and edited for Infoworld, InformationWEEK, LinuxInsider.com, and many other business and technical publications. She is now Domino's Content Director.
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