DataAware
Newsletter

July 2025
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This month, we’re diving into the hottest takes in data (and a few cool-headed truths that’ll actually make your job easier).

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But first—a little game to kick things off:

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🔥 Hot Take or Hard Truth?

Ascend.io

🔥 Hot Take or Hard Truth?

Test your knowledge of the data community!

Question 1 of 5

"More data professionals actively DISTRUST the accuracy of AI tools (46%) than trust them (33%)"

💎 Hard Truth!

According to the 2025 Stack Overflow Developer Survey, 46% of developers actively distrust AI tool accuracy while only 33% trust it. Only 3% report "highly trusting" AI output, with experienced developers being the most cautious (20% "highly distrust" rate). This widespread skepticism reflects the need for human verification in professional development work.

Question 2 of 5

"Python usage for data analysis DROPPED from 51% in 2022 to 44% in 2023"

💎 Hard Truth!

The JetBrains Python Developer Survey revealed that Python usage for data analysis indeed dropped from 51% in 2022 to 44% in 2023. Similarly, machine learning usage dropped from 36% to 34%. This trend suggests the data science field may be diversifying its toolset or that other programming languages are gaining ground in specific use cases.

Question 3 of 5

"Poor data quality costs the US economy around $3.1 TRILLION per year"

💎 Hard Truth!

According to IBM research, poor data quality costs the US economy approximately $3.1 trillion annually. Additional studies suggest that data quality issues can result in up to 40% revenue loss for businesses. The 2025 State of Data Quality survey also found that data downtime nearly doubled year-over-year, with a 166% increase in resolution time.

Question 4 of 5

"Only 37% of managers wish their direct reports had more data science skills"

🔥 Hot Take!

This is actually a significant understatement! The 2024 Gallup Math Matters Study found that 37% of managers specifically identified data science as a desired skill for their direct reports. However, 85% of managers wish their employees had one or more additional math skills overall, including financial math (41%) and foundational math (41%), showing the true demand is much higher than "only 37%"!

Question 5 of 5

"15-year-old pandas is STILL used by 77% of data professionals despite newer alternatives like Polars"

💎 Hard Truth!

Despite being 15 years old, pandas remains the dominant data processing tool with 77% usage among respondents doing data exploration and processing. Meanwhile, the faster Polars (which reached v1.0 in 2024) is used by only 10% of respondents. The staying power of pandas reflects its mature ecosystem, stable API, extensive documentation, and the power of being first to market in the Python data science stack.

🎉 Quiz Complete!

0/5

Thanks for testing your data community knowledge!

📊 Key Takeaways:

The data community is rapidly evolving with AI tools gaining adoption despite trust concerns, established tools like pandas maintaining dominance, and data quality remaining a trillion-dollar challenge. Stay curious and keep learning! 🚀

Ready to build smarter data pipelines? Learn how Ascend.io's agentic data engineering platform can automate your data workflows and accelerate your team's productivity.

Webinar Recap

From Old School to Agentic: Agentic DataOps

Catch the recording of our latest webinar on Agentic DataOps— where we explored how AI is empowering teams to automate the tedious manual work that comes with driving effective operations.

What we covered:

How good DataOps foundations can drive powerful agentic assistance
The 3 key ingredients agents need to actually take on meaningful work
A live demo of Agents that monitor pipelines and triage incidents

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See Agentic Data Engineering In Action →

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Upcoming Events

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WEBINAR: Practical AI For Data Engineering

Wednesday, August 27, 2025

10am PT | 1pm ET

Tired of vague promises about AI changing everything? So are we.
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Join GigaOm analyst, Andrew Brust, and Ascend.io Founder and CEO, Sean Knapp, for a no-nonsense discussion on where AI actually fits in modern data engineering workflows and what teams need to look for when putting these tools to work.

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What we're reading:

🧠 Build Your Own AI Agents
Want to go beyond generic LLM helpers? Learn how to build custom agents using Claude Code, and learn about how you can build similar agents within the Ascend platform that do mor ethan just write code.

Read the Post →

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🤖 Meet Your New (Favorite) Teammates: DataOps Agents
Forget babysitting pipelines. This post breaks down how intelligent agents can automate ops work from deployments to incident response—so your team can stop firefighting and keep building.

Read the Post →

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👋 That’s it for this month—whether you’re melting in the heat or chilling in your AC-powered command center, we hope your pipelines stay cool and your takes stay spicy. Catch you next month with more insights.

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Until next time,
✨ The Ascend Team

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DataAware Newsletter

🔥 Hot Take or Hard Truth?

📊 Key Takeaways:

Webinar Recap

From Old School to Agentic: Agentic DataOps

Upcoming Events

What we're reading:

DataAware
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