Most enterprise leaders recognize that data science and related disciplines are essential for competing in the modern economy. But many have struggled to mature and scale their data and analytics efforts.

According to IDC, organizations that are in the top quartile for enterprise intelligence (i.e., outstanding data science and business analytics capabilities) “are 2.7x more likely to have experienced strong revenue growth between 2020 and 2022, and 3.6x more likely to have accelerated time to market for new products, services, experiences, and other initiatives.”

Forrester refers to these organizations with excellent data science capabilities as “advanced insights-driven businesses.” And it noted that only 7% of companies met the criteria for that moniker in 2021. It predicts, “The decisions made in 2023 will fuel or extinguish a world of insights opportunity. With an uncertain 2023 approaching, data teams sit atop a tipping point that looks like rollercoaster carts gathering on a straightaway before the drop -- only data teams with their partners, practices, and platforms lined up and prepared will move with speed and efficiency in the uncertain year ahead.”

Many teams hoping to achieve the necessary level of preparation are evaluating their current data science technology stack and considering making changes.

Today many teams are using a wide range of different tools. Gartner notes, “Analytics portfolios are becoming increasingly complex as a result of cloud migrations, new and disconnected ecosystems, and emerging self-service demands.” And it predicts, “By 2023, ease of migration, interoperability and coherence will be deciding factors in 90% of data science, machine learning, and AI platform buying decisions.”

So which tools will data leaders be evaluating when looking for interoperability and coherence and making those buying decisions?

This slideshow highlights 10 of the most popular data science tools available today. It includes data science platforms, programming languages, and other tools that can help enterprises become more data driven.