#28. Enabling Reliable Analytics Everyone Can Trust with Megan Dibble

Episode 28 of the Humans of AI podcast, hosted by Sheikh Shuvo, titled "#28. Enabling Reliable Analytics Everyone Can Trust with Megan Dibble" was published on December 12, 2023 and runs 18 minutes.

December 12, 2023 ·18m · Humans of AI

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Summary

In this episode of Humans of AI, Megan Dibble, a data journalist, shares her journey from industrial engineering to data analysis and her role at Alteryx. She discusses the importance of trust in data and how Alteryx enables reliable analytics for everyone. Megan also talks about her experiences hosting the Alter Everything podcast and the surprising insights she has gained from interviewing data practitioners. She shares her process for finding inspiration for her data journalism work and highlights the areas of data science she is currently focused on. Megan concludes by offering advice for early career data analysts.TakeawaysData journalism involves creating content about all things data, using various mediums such as writing, podcasting, and social media.Choosing a career in data analysis can involve inflection points, where individuals discover their passion for working with data through internships and job experiences.Data analysts and journalists should prioritize trust in data by using tools that provide transparency and governance, and by starting projects with clear business problems.The Alter Everything podcast has revealed the diversity of backgrounds in the data field and the importance of starting data projects with a clear business problem.Data journalists find inspiration from various sources, including courses, reading publications, and their day-to-day work experiences.Areas of focus in data science include data ethics, bias in algorithms, and the limitations of quantification.Early career data analysts should avoid taking on the weight of an organization's data structure and instead focus on building relationships with IT and data engineering teams.

Episode Description

Takeaways

Data journalism involves creating content about all things data, using various mediums such as writing, podcasting, and social media.
Choosing a career in data analysis can involve inflection points, where individuals discover their passion for working with data through internships and job experiences.
Data analysts and journalists should prioritize trust in data by using tools that provide transparency and governance, and by starting projects with clear business problems.
The Alter Everything podcast has revealed the diversity of backgrounds in the data field and the importance of starting data projects with a clear business problem.
Data journalists find inspiration from various sources, including courses, reading publications, and their day-to-day work experiences.
Areas of focus in data science include data ethics, bias in algorithms, and the limitations of quantification.
Early career data analysts should avoid taking on the weight of an organization's data structure and instead focus on building relationships with IT and data engineering teams.