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A Roundup of Blogs and Newsletters About Analytics - Issue 133
My favorite blogs and newsletters to read about data and product analysis, data science, and data engineering.
Hello, and welcome to my Data Analytics Journal, where I write about product analytics and data science.
If you’re not a paid subscriber, here’s what you missed this month:
How To Measure Your Adjacent Users - A walkthrough of an important product persona and SQL solution on how to locate them in your user base. A direct look at why product analytics tools still fall short to support you in such analysis.
Applying ML in Product Analytics - There are over 50 types of ML algorithms. Here is a guide to help you decide which ML model to pick in order to create a customer churn prediction model or forecast subscription revenue.
When Simple Becomes Tricky: SQL CASE Statement - re-introducing the concept of CASE statements to remind all of us how easily mistakes can slip in and become overlooked.
There are many great newsletters on ML and data, but not that many on the classic old respected data analysis that fuels product, finance, branding, marketing, and more. Today I’ll share the top blogs and newsletters that I believe are a must-read for every analyst or data practitioner across data analytics, product analytics, business, finance, data science, deep learning, and data engineering.
The Top 10 Best Blogs For Analytics
Avinash’s blog remains the best resource for digital marketing and analytics. I have been reading Occam’s Razor for too many years now and have adopted many analytical concepts from him. I have so much respect for Avinash. Having such experience, authority, and reach (Analytics Evangelist at Google for 15 years!), he continues raising the bar for all of us by regularly publishing hands-on, practical, and applied concepts with examples and case studies. This is so rare. Many experts who reach high status prefer writing rather soul-searching existential philosophies (Run your own race, The past is not precious, The Two Things to Do. When You Don’t Know What to Do), and yet Avinash stands out by continuously bringing applied concepts, how-tos, and breaking popular myths by reminding us the math, logic, and foundations of analytics. I am excited about his new adventure at Croud, which, hopefully, will be shared with us in his upcoming publications. 🚀
Also, I highly recommend his book Web Analytics 2.0 on how to develop a strategy and apply techniques to measure marketing campaigns and experimentation.
When you are Chief Analytics Officer and a founder at Mode, you can afford to burn bridges, create controversy, and spill the tea. His newsletter proves that having an unoriginal blog name, an unfriendly long-read, and an unforgivable amount of references won’t limit your reach and popularity if you truly love analytics. While I am not a fan of Benn’s chosen publication format, nor do I always agree with many concepts he shares, his newsletter has been my pleasurable Friday night read for quite some time. There is a lot said between the lines in his articles, and his messages are best paired with multiple glasses of wine. It’s always an adventure with his publication.
A dashboard lifecycle vs the old Land Cruiser? 2,000 words to say that storytelling is more important than math? Is he really using the Bible and religion to talk about ChatGPT? BI is dead, but Tableau apparently is not. Suspense. Are we analyst, or are we melon? Wait, what in the…🤯
The weekly newsletter on mobile growth covers industry trends, mobile metrics, app teardowns, and analytics for the top apps of the week, breaking down their growth with data, insights, and analysis. This has effective visualizations in concise and readable formats. Ariel also has a YouTube channel where he analyzes the mobile app growth covering subscriptions, activations, top of the funnel, onboarding flow, experimentation, and more. This is a crucial resource if you work with mobile analytics, which is still new for many of us. Analyzing mobile activity lifecycle is different from the web and requires a slightly different analytical perspective and skill set. Ariel does amazing work on asking the important questions, focusing on the right metrics, and creating a resource for us to uplevel mobile analytics. Big fan.
A VC, investor, blogger, and SaaS mastermind resides on Medium. Christoph Janz is Managing Partner at Point Nine Capital and has been writing about SaaS, early-stage investing, growth, and metrics quite a bit (and since the dark ages, before Twitter was created). His publications and talks set the foundation for today’s SaaS analytics. He was one of the first to introduce cohort analysis and talked about the importance of customer segmentation (which I graciously adopted and use a lot). His articles are a must-read to learn the complexity of churn, LTV, and freemium, and understand all connections between KPIs and their direct and indirect impact on growth. What makes Christoph different from many data-driven VCs, advisors, and blogger-investors is his ability to merge the classic financial sales-driven concept of growth with a modern disruptive product-led mindset, and how he can translate it into an easy-comprehend template, chart, or publication (or a napkin).
Learn the art of blogging, the German way - prove a hypothesis via applied correlation analysis, linear regression modeling, causal inference, and plotting to illustrate a strong (and positive!) storyline. Simple, correct, and precise. ⭐
A weekly newsletter about “quantitative work” covers data collection, data cleaning, and research. It’s written by Randy AU, a Quantitative UX Researcher. I believe that Randy comes from the same “old-fashioned” generation of analysts as I did, who were trained to invest in data quality and due diligence via myriad checks, processes, frameworks, creating baseline metrics, code reviews, and more. His writing and direct look into research methods resonate with me and is often a breath of fresh air among many fancy tooling and solutions blogs.
His recent piece is a masterpiece and has to be taught at every data school - How do we actually "pull stories out of data"? 😍
The biggest newsletter on product, growth, and people management. It’s always interesting to see what PMs are up to, and how to influence them.probably thinks his audience either lacks the skill of basic deduction or is too busy to learn - he does an outstanding job breaking down every point until it’s super clear so that even your dog could understand it. And even if you still don’t, he generously provides so many examples for every use case to ensure you can take value from it.
In case you haven’t seen the best article in his newsletter yet - How to measure cohort retention. 😂
A weekly newsletter is written bywith a mission to demystify the data space, cover the modern data stack, and bridge the gap between data people and non-data people. Arpit runs The data beats Show podcast and a YouTube channel. What I like about this newsletter is that Arpit does a great job breaking down CDP, CDC, ETL, GTM, common data concepts, databases, and more, making the complex simple.
Check his Data Beats Tools Directory. It is quite cool, with most data tools nicely structured and described.
I learned about this weekly newsletter and its charismatic writer,, a few months ago, and didn’t miss an article since then. This is your Finance 101, carefully peeled, processed, and nicely served with sprinkles. A must-read for analysts, and I highly recommend subscribing to anyone who interacts or works with financial metrics or KPIs. The newsletter covers a wider landscape of topics including product, marketing, investments, equity, industry trends, and more.
I wonder if there is a way to request a deep dive into EBETA and its benchmarks 🤔.
This is a good resource for ML, NLP, deep learning, and computer vision with a new look. It’s been around for ages, and it keeps advancing as more and more great authors continue to join the lead. I keep recommending them every year. This is my go-to resource for statistics or ML problems. With a lot of great materials published, it’s hard to navigate through the site, so I keep bookmarking my favorite templates and sheets.
Make sure to check out their Glossary of common statistics terms. Very helpful.
I have been a fan of Jay’s newsletter and his YouTube channel for a few years now. His newsletter offers interviewing tips and prepares you to land the dream data science or analyst job. He regularly sends out quizzes and exercises, mostly in Python and SQL, aimed at product intuition, algorithm, analysis, statistics, probability, and modeling.
If you are currently interviewing, start with his Company Interview Guides.
And, of course, my favorite newsletter of all time, Chartr is an ocean of data in one slide. They use best practices of data storytelling so simply and effectively. A newsletter to get inspired by. ❤️
Other top blogs on my list across deep learning, data engineering, and product
because sleep is overrated
Haki Benita's Blog is about databases, SQL, performance tuning, query optimization practices, and more. Very nicely written. Aside from writing, Haki also stays busy with coaching, developing tutorials, running training sessions for O’Reilly, and much more. Did you see his Practical SQL for Data Analysis? Timeless.is a monthly newsletter with deep dives into data tools, methodologies, and languages written by , a data influencer. If you have the patience to wait for his newsletters, you’ll be entertained by a direct and unbiased look into data mesh, metrics layer, arch design, dbt, and more. This is my place to go to learn about identity resolution, data mapping, and data linkage and to understand how it impacts analytics. And btw, this is the best article on the semantic layer out there Deep Dive: What The Heck Is the Metrics Layer. 🤩 is written by someone located not in Seattle but in Colorado. The weekly newsletter is run by Ben Rogojan, a YouTube data influencer who runs his data infrastructure consulting firm. This is a must-read for every data engineer as covers all essentials and nuances of daily data engineering life and routine. For us, analysts, I keep an eye out mostly for 3 things in his newsletter: (1) data industry trends and his data catalogs, (2) databases overview, and (3) data horror stories to be prepared for being unprepared.
Postgres Weekly - a weekly email round-up of Postgres news and articles. While the main theme of the newsletter is to advocate for all things Postgres, I love their round-up on how-to publications: how to install a database, how to work with RANK() in SQL, window functions breakdown, SQL performance guidance, and more. If you work with SQL, I highly recommend subscribing.
R Bloggers - Everything you could want to know about R, written by R users (if you are still using R).
Pylenin.com is another good Python newsletter but more focused on beginners. You will find a good description of data types, and simple data transformations with many examples.is my favorite newsletter on deep learning, not because of its amazing name but also for the easy-to-read format, structure, and nicely curated list of news published every Sunday. It offers the right sources to learn and stay in a loop of recent LLM, NLP, and ChatGPT advancements. Analytics engineering is on the rise, and in over a year it became a massive community and movement pushed by modern data products. It is transforming both data engineering and analytics roles. While the world is trying to figure out and divide the ownership of managing data pipelines and Q&A between analysts vs data engineers, it’s a good resource to follow to learn and stay on top of all the movements in the data space.
Data Is Plural - a slightly different and “unique” weekly newsletter with a list of datasets across different topics and industries published by Jeremy Singer-Vine, a data journalist and storyteller (ex-writer for The Wall Street Journal, ex-data editor for BuzzFeed News). It’s priceless for analysts and researchers who are looking to develop their portfolios, work on SQL and Python, or simply have curiosity and time. All datasets he shares are free and open. Go wild.
Reforge Blog publications are at the intersection between product and strategy, but a further step into product analytics. Every Reforge publication is developed around the importance of being data-driven and developing your strategy on top of data inputs.I learned about this newsletter recently and it’s been a light, fun read every Sunday. George runs a curated resource on processes, products, and frameworks aimed at product managers. I can pretend I am one and appreciate his resources, lifehacks, and memes, and continue to wonder why would someone name a newsletter using 1-1-2-3 and not 0-1-2-3. Oh yeah, and I bookmarked the CIA Guide on How to Sabotage at an Organisation.
Department of Product a weekly newsletter about product and analysis. More about a product, and less about analysis, but some articles are good. Expect topics around product strategy, discovery, design, tools, launches, and some sparks of analytics in between.
The Ravit Show Newsletter is a weekly newsletter with insights about the latest news on data, AI, events, books, and tons of free resources. So if you know what you are looking for, this is the best resource to use. And if you don’t, they have a Slack community channel to help you figure out what you need help with.
Through the Noise - a weekly Sunday newsletter about AI and tech “without the noise” written by Alex Banks, co-founder of Tribescaler (it has something to do with AI and viral tweets). While I don’t quite use yet their awesome tweet auto-generator, I do enjoy Alex’s newsletter which has a curated list of news on deep learning and AI. I follow it for ChatGPT updates, AI predictions, and startup spotlights.
My biggest respect and appreciation goes out to all of the amazing writers. Thank you for continually publishing strong content.
Thanks for reading. Until next Wednesday!