ABOUT THIS PODCAST 🔗

Update frequency:
every 22 days
Average audio length:
65 minutes
English
United States
30 episodes
since March 7, 2021
episodic
explicit content

LATEST EPISODE 🔗

Some of our topic highlights include: Confidence intervals and precision needs vs wants The Spam bot problem and issuing corrections Shipping to vision vs shipping to need (and knowing when to say no) Market-based economy for data asks  The Microsoft SQL servers con Analytics-driven change rather …

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Some of our topic highlights include: His background and path to founding Montreal Analytics The importance of investing in your data Why clients trust Cyril and his team How Montreal Analytics leads organizations in the right direction Learning through trial and error Whether a shared data stack …
Some of our topic highlights include: The right amount of precision in different scenarios What modern sales is (and what you need to be successful) Why salespeople are crucial to your customers  Using automation to inform sales behavior The trick for identifying talent before you have the data an…
Some of our topic highlights include: How Sarah got into the world of data Data modeling vs data building (and depth vs variety) The organizational pieces that need to fall in place before you get to the science in data science How experience in sales helps with technical product translation Why S…
Some of our topic highlights include: Emily’s background, her journey to data, and what she does at Drizly Answers to your burning questions, like: What type of alcohol is the most popular? How Emily moved up the data ranks from engineer to manager Value of optimizing old vs building new The evolu…
Some of our topic highlights include: Jessica’s early career in banking Differences between data across different types of companies How data roles differ from consumer banking to investment banking  The importance of statistical rigor and running experiments The art of persuasion and corporate ps…
Some of our topic highlights include: Scott’s journey to becoming “unhireable”  Why management consulting is so intense Why you need tool conventions The risk of analysis paralysis The value of career learning vs salaries To what degree trust is earned through work and wisdom rather than title or …
Some of our topic highlights include: How CoderPad approaches technical interviewing for their data team What makes running technical interviews at most organizations so difficult How we, as interviewers, can do a better job at helping candidates see we’re on the same side What analytics teams sho…
Some of our topic highlights include: The history of dbt Labs (and the dbt community) How community became an opportunity for the dbt Labs team to transfer their internal culture and values outward (and how they did so)  The original vision and purpose behind the dbt community (and how it’s mature…
Some of our topic highlights include: The history and background of Monte Carlo Why the planning process is so important for data teams How to set (and crush) a data goal The difference between being obsessed with systems and being obsesses with goals How data teams waste time How often data downt…
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