Top Ten Quick Takes From The Past Month - Issue 20
A recap of my newsletters over the past month.
Today I celebrate 5 months of writing, publishing, and advocating for old-fashioned genuine data analysis. 5 months of late-night research, doubled coffee intake, and a great community of analysts created from my amazing readers ❤️
To celebrate this small (yet important!) anniversary, I prepared a special issue for you today.
Besides a usual recap of my newsletters over the past month, I am so excited to share my recent interview with one of my favorite bloggers, growth hackers, and influencers: the one and only Brain Balfour, Reforge Founder/CEO!
🧭 Expert Spotlight with Brian Balfour, Reforge Founder
If you are working within the fields of tech products, marketing, or data, you probably know about Reforge. As someone who has been working with product growth methodologies for many years, I can’t highlight enough how important and useful Reforge frameworks are for deep dives, guides to help you improve retention, running experimentation, or monetization. If you have been reading my journal, you might notice I often highlight Regorge concepts and insights in my newsletters (Benchmark traps, Adjacent user, the Word of Mouth Coefficient). I am so honored and excited to reach its founder Brian Balfour to interview him for my journal.
Read the full interview with Brian to learn what the common challenges data analysts are dealing with, how to navigate through them, and how to best differentiate yourself and develop your career.
Ideally, you are part of a truly cross-functional team working alongside product managers, engineers, designers, and not an order taker when a question or request comes up.
Many people pick a generalist side and do a little bit of each. The problem with that is it’s difficult to go deep, and as a result, you end up looking like all other analysts. Career management is Economics 101 - supply-demand. How would you put yourself in a situation where you are very low supply, and there is very large demand. And that’s how you get the roles and the job opportunities faster than others do.
I wish I had learned this many years ago. Good mentors and coaches are priceless.
✨ 10 Quick Takes From Last Month Newsletters:
Read the recent post from Netflix Technology Blog about Analytics at Netflix: Who We Are and What We Do. It’s an interesting view of Analytics and Visualization Engineering at Netflix, how they structure the team, what their business verticals are, how they define analytics, and what their common projects and responsibilities are.
Churn. Churn. Churn! How to reduce churn is asked in every interview for a SaaS company. To know that, you must have a thorough understanding of the churn rate and how to tackle it through the business or product lenses. Make sure to read this recent walkthrough on how to approach and understand churn, as well as some examples of how churn is calculated at different companies.
My first interview in November was with Wes Bush, the bestselling author of "Product-Led Growth: How To Build a Product That Sells Itself". He is the founder of the Product-Led Institute and is best known for challenging the way SaaS leaders approach growth. Read the interview about the SaaS trend, challenging metrics like churn, PGLs, benefits of product-led growth, and product analysis.
SQL practice: CASE is a common conditional expression similar to if-then-else statements. It is supported by all SQL databases (Oracle, MySQL, SQL Server, etc). Using CASE statements for SQL challenges during the technical interview demonstrates solid SQL understanding, so I highly encourage using it for filtering and specifying conditions and expressions. Learn how to apply it here.
The best 16 books to learn SQL - a roundup of the best books on SQL (from beginner to advanced level) from the DataPine blog.
Check out this video of the most popular databases from May 2006 up to today. In October 2020, the most used and popular databases are Oracle, followed by MySql, and then SQL Server. Who knew?
Borrowing from another blogger, this is an awesome resource on best books, courses, and practices on data engineering - Awesome Data Engineering. Big thanks to the author Snir David for putting it together.
If you are looking for a rich textural dataset for NLP or other ML, check these 100,000+ books in plain text format (37GB). You are welcome.
Take advantage of WooTech, a mentorship platform for women in technology that guides them in their careers. It is open to everyone including males, students, working professionals, or just anyone curious about technology.
This month was tough and intense. Get some dose of cuteness from Koala Webcam from San Diego Zoo! 😍
🍸 Drink and Mingle
Upcoming free events, meetups, talk, and webinars.
Nov 25, A Brief Introduction to ML
Nov 27, Breakathon - 48-hour hackathon
Nov 30, Adventures with a wine data set
Nov 30, Power BI Data Modeling
Dec 8, DSS: Applying AI & ML to Finance & Tech
Dec 14, WWC: Fair and Explainable AI
If you missed my previous newsletters, here are the links:
November:
October:
September:
5 Concepts Of Data Engineering Every Data Analyst Must Know - Issue 11
How To Choose The Correct ML Algorithm For Your Problem - Issue 9
August:
July:
The Meow cyber attack and statistics for data analysis - Issue 3
Taking Off: Scaling User Growth - Expert Insight + SQL - Issue 1
Thank you all again for your support and for sharing this ride with me.
Until next Wednesday! And Happy Thanksgiving!