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Cassie Kozyrkov Profile picture
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May 18 • 9 tweets • 2 min read
As a #DataAnalyst, your best north star for skills development is... speed! 🧵
Don’t be fooled by a simplistic interpretation of speed. A sloppy analyst who keeps falling for shiny nonsense “insights” will only slow everyone down in the long run. "Speed" means something nuanced. 🧵
Analysts must master many different forms of speed, including:
Speed of getting data that’s promising and relevant. (Domain knowledge.)
Speed of getting data ready for manipulation. (Software skills.)
Speed of getting data summarized. (Mathematical skills.)
...continued...🧵
More kinds of speed for analysts to master:
Speed of getting data summaries into their own brains. (Data visualization skills.)
Speed of getting data summaries into stakeholders’ brains. (Communication skills.)
Speed of getting the decision-maker inspired. (Business acumen.)
🧵
The data landscape is changing rapidly, so you can’t afford to stagnate. The tools you use today won’t stick around for long. Keep sharpening your claws, but don’t chase the buzzwords. 🧵
There are a lot of insecure people who don’t know how to make themselves useful so they put all their effort into titles, certificates, badges and other baubles. You’re better than that. 🧵
Stop asking: “Should I learn this tool/method/technique that all the cool kids are talking about?”

Start asking: “Will learning this make me faster?”

🧵
Learn whatever makes you faster (in all the ways that matter). Since your work involves accelerating others, start by accelerating yourself. 🧵
More career advice for analysts in the article: bit.ly/quaesita_fasta…

#DataScience #Analytics
🧵

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More from @quaesita

Cassie Kozyrkov Profile picture
Apr 27
In a #DataScience project, all paths lead back to #Analytics, often with messy inherited data - here are some helpful skills and traits for it, a thread 🧵
🔥domain knowledge🔥helps data scientists and analysts make sense of the chaos and guide their judgment about how to spend their time and effort. 🧵
🔥data design skills🔥help data scientists and analysts inform data collection efforts based on what they’ve discovered. 🧵
Read 12 tweets
Cassie Kozyrkov Profile picture
Jan 4
A decision scientist's 2 tips for new year's resolutions involving diet and exercise, a thread. 1/🧵
Diet tip: Calibrate your evaluation window. If you have a resolution to reduce intake of something, don't evaluate your success by comparing today with yesterday. 2/🧵
A day is an arbitrary unit, so why not optimize your evaluation window? A day seems natural, so many people don't ask themselves if it's the best unit. But if you use a shorter window, your chance at a "fresh start" comes sooner. 3/🧵
Read 22 tweets
Cassie Kozyrkov Profile picture
Oct 19, 2021
Leaders! Stop dropping the ball on #machinelearning projects!

This thread is a manual for the leader's role in ML/AI projects, with short guides to each bit. 1/🧵
If you think it's okay for the leader to skip these tasks or punt them to the #AI project's chief nerd, read this: lnkd.in/eziSYhX
2/🧵
lnkd.in/eziSYhX
First, check that ML/AI is right for you. Don't just chase the buzzword. Use it to solve a real problem! Here's how:
3/🧵
Read 15 tweets
Cassie Kozyrkov Profile picture
Jan 15, 2021
1/🧵 Good #DataScience advice that breaks pretty much every rule you learned in class... a thread. (+full blog post linked)

English version: bit.ly/quaesita_rethi…
Spanish version: bit.ly/spanish_rethin…

#AI #MachineLearning #Statistics #RStats #agile

bit.ly/quaesita_rethi…
2/🧵 Allow your approach to be sloppy at first and burn some of your initial time, energy, and data on informing a good direction later. That's right, you're supposed to start sloppily ON PURPOSE.
3/🧵 Have a phase where the only result you’re after is *an idea of how to design your ultimate approach better.*
Read 16 tweets
Cassie Kozyrkov Profile picture
Jan 13, 2021
What are the 5 most important questions to ask when starting with a new dataset? A video ( + a thread 🧵)

bit.ly/quaesita_yt5da…
#1 - Purpose

What was the purpose for which this dataset was collected?
#2 - Competence

How competent were the people who collected this data?
Read 7 tweets
Cassie Kozyrkov Profile picture
Aug 14, 2020
What makes an analyst excellent? Speed! But that's not as simple as it sounds. They need 6 kinds of speed... 1/🧵

#DataScience #Analytics #rstats #DataAnalytics

bit.ly/quaesita_speed
1) Speed of getting data that’s relevant. (Domain knowledge.)
2) Speed of getting data ready for manipulation. (Software skills.)
Read 15 tweets

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