Break the data science talent bottleneck

The data science talent gap is ever-increasing. Domino empowers “low code” analysts and data scientists to work in R and Python alongside more advanced data scientists. That unlocks more capacity for your team, while upskilling your workforce.

• Analysts who learn code can advance their careers into data science, improving recruitment and retention.
• Data scientists can easily mentor and collaborate with analysts since everyone is speaking the same language(s).

Data and analytics leaders are under greater pressure to deliver value than ever before. No-code options just haven't lived up to their promise, leading to siloed projects, limited talent pools, one-off insights, and POCs that never make it to production. Leading organizations are shifting their focus to building a broad talent base of analysts with Python, R, and other coding skills.

• Code is fast, flexible, transparent, and efficient to write, edit and reuse.
• Python and R are the gold standards for analysis and data science.
• Data science innovations are created with code.

Data and analytics leaders are under greater pressure to deliver value than ever before. No-code options just haven't lived up to their promise, leading to siloed projects, limited talent pools, one-off insights, and POCs that never make it to production. Leading organizations are shifting their focus to building a broad talent base of analysts with Python, R, and other coding skills.

• Code is fast, flexible, transparent, and efficient to write, edit and reuse.
• Python and R are the gold standards for analysis and data science.
• Data science innovations are created with code.