Domino Data Lab Announces Domino Code Assist to Help Close Data Science Talent Gap and Democratize Advanced Analytics

Revolutionary new product for Python and R users unifies work of low-code and expert data scientists in one platform with professional-grade tools for all users

Domino Data Lab, provider of the leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, announced the general availability of Domino Code Assist (DCA), a groundbreaking new product for business analysts that enables enterprises to rapidly close the data science talent gap and democratize data science. With DCA, Domino Data Lab enters the low-code space to elevate business analysts using Python and R into the data science world.

Described by the Harvard Business Review as “the sexiest job of the 21st century,” data science roles are projected to have a growth rate of 36% by 2031, according to the U.S. Bureau of Labor Statistics. DCA enables Chief Data Officers (CDOs) and Chief Data Analytics Officers (CDAOs) to involve more analytics professionals in data science and machine learning projects using a code-first strategy. At the same time, by generating the code which helps business analysts learn and grow, DCA offers them an opportunity to learn valuable coding skills and helps an organization develop new data science talent from within, all while improving efficiency of both business analysts and data scientists.

Domino’s unique code-first approach to low-code data science allows business analysts to generate code rather than using a black-box tool or proprietary drag-and-drop interface. This allows data prep, dashboards and models to be transparent and portable while enabling business analysts to collaborate with advanced data scientists in the same languages and environments scientists work in.

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“Python is the new Excel and Domino Code Assist is about pushing the adoption of code-first data science in a way that has not been conceived of before,” said Sean Otto, PhD., Director of Analytics at AES Corporation. “By enabling both our advanced and low-code team members with a common platform to deliver AI and ML with Domino, we can accelerate the innovative use of our data across a wide variety of technical and non-technical data practitioners and data-adjacent parts of our business.”

“Domino Code Assist is a game-changing opportunity for CDAOs and all analytics executives who strive for growth and expansion in their data science talent and culture,” said Nick Elprin, co-founder and CEO at Domino Data Lab. “I am excited to witness the impact this new superpower will bring in solving the most challenging business problems faced by enterprise data science teams.”

Enabling a Code-First “Pyramid” Strategy

With DCA, enterprises can pursue a code-first “pyramid” or “mosaic” data science talent strategy: leveraging a select group of highly skilled experts and larger numbers of less advanced members who still write some code. With everyone working in code on the same platform, organizations maximize the value of experts, while enabling and empowering analytics professionals at all levels.

“No-code solutions with drag-and-drop interfaces are appealing at first because they promise an easy path to data science, however, their limitations can prove frustrating for unlocking the full value of data, and the inner workings of analytics solutions are often a ‘black box.’ This leads leaders to skepticism and mistrust around insights for business-critical decisions,” said David Stodder, Senior Director of Research at TDWI. “Building a code-first talent pyramid connected by shared data science programming languages improves data science collaboration, the mentorship of newer data scientists, and ultimately increases workload capacity while accelerating transformation into a true data-driven organization.”

By empowering a broad range of data science and analytics professionals to unlock the power of data in a single platform, DCA helps CDOs, CDAOs, and their staff address three key elements of democratizing AI:

First, DCA helps address the “cold start” problem by reducing time-to-insight for everyone:

• Business analysts can use wizards in DCA to automatically generate standard Python and R code for data ingestion, preparation, visualization, and app creation tasks. They can also review other models and analyses as the starting point for their work, and to help learn the necessary commands and syntax.
• For data scientists, DCA boosts productivity by eliminating the need to write code and remember the precise syntax for repetitive tasks. This frees up precious time for higher-value work.

Second, DCA exposes low-code business analysts to well-written code:

• It generates standard, editable Python and R code for common tasks.
• Business analysts get a repository of existing work for use in helping ensure that their work is consistent with the rest of the team. They can also easily collaborate with more experienced peers and mentors.
• All team members can save snippets of code as wizards to share across the organization, increasing code re-use, best practice adoption, and standardization efforts.

Third, DCA helps align all data science work with broader governance, prioritization, and review processes.

• Data-savvy analysts and other non-data scientists can safely gain the professional data science skills they need.
• With DCA, less-experienced analysts’ can have someone more seasoned review their work to ensure that the datasets are being used appropriately, the model was trained correctly, the project is scoped properly and aligned with organizational priorities.

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Domino Welcomes a Top-Notch Low-Code Leader

Domino also announced that former Plotly co-founder and CEO Jack Parmer is joining the Domino team. Parmer, who was instrumental in bringing the Dash framework for Python to market, will ideate and execute major new product strategy initiatives in close collaboration with Domino’s customers and leadership team.

“Domino is hands-down the leading platform for enterprise data science among the Global 2000,” said Parmer. “I’m thrilled to leverage my experience in building Plotly to help Domino’s customers solve for the AI talent gap with a code-first strategy to democratize AI using Python and R analytics.”

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