Goodbye 2021🎄 - Issue 75
Some of the best publications, some gratitude, and heaps of confetti
Hello dear readers, this is the last newsletter of the year!
❤️ Thank you so much to my mentors, friends, supporters, and all my readers. You inspire me to write this journal. Every newsletter develops more connections with my audience, and I believe that we can all together drive and advance the current state of analytics, bringing more visibility to it, with the hope of creating and developing better data-driven products and services as a result.
A half year ago I was celebrating a year of writing wherein I shared the reasons for writing this newsletter, my team, mission, and learnings.
To add to that, I would like to report that I take profound offense when I hear that being an analyst today is not “cool”. A correction: to be a mediocre analyst today is not cool. A mediocre analyst is an analyst who expects the data to be clean and nicely packaged in some sort of data mart and then proceeds to get lost when no structured data or easy-to-read data is available. It’s the type of analyst who is locked into a Tableau workbook, generating continuous data puking (putting a pile of color-coded variables into one chart) without the ability to simplify or break that data down.
Creating an analytics legacy, making a company truly data-driven, owning data governance, and setting the right frameworks based on the proper foundation are all challenging and exciting. It doesn’t happen overnight, and sometimes takes years to bring data into decision-making and business strategy. In my journal, I want to create a ladder showing how to get there. I want to encourage and inspire my fellow data analysts to enjoy genuine analytics and build a data heritage at your company that you would be proud of.
🏆 Grow and upskill
Over the years, I’ve created a lot of checklists, playbooks, and code snippets. This journal is a place for me, first of all, to store, keep, and reread this type of content. My favorite articles across different domains, best frameworks, good examples, gotchas and caveats, reminders, calculations, and definitions - all of which are based on my own experience, learnings, or research of best practices and working solutions. I put it all up here for my subscribers to reuse and, hopefully, upskill and grow (or curse me! You never know).
I’m honored to have thousands of readers around the world with different levels of knowledge and experience, from experts to beginners, or people transitioning into the world of data from other fields, and across all industries.
Data analysis is a challenging field, still emerging and always transforming. Navigating through it is tough and exciting. I’m grateful to everyone who is reading my newsletter. I hope it can help you find a path for professional growth, point you to the right sources and documentation, and inspire you to learn and love data analysis.
💰 Spend Your Annual Training Budget
With the end of the year almost here, it can be time to spend any unused training budget allocated to your team. Paid subscribers receive:
SQL and Python interview questions, solutions, and guidance.
Interesting and tricky deep dives and case studies.
Data analysis projects examples and walkthroughs.
A/B tests approach, real-life scenarios, and implementation.
Insights from data analysts and data science experts who walk us behind the scenes of their daily work, challenges, and share their learnings.
Interesting stories about how data affects people’s lives and how data analysts make a change.
Additionally, paid subscriber questions and support are prioritized.
You can cancel anytime. And, you also can expense the subscription.
If you are currently looking for a job, and can’t expense or afford the subscription, just email me and let me know. Hopefully, my journal will help you land a job (as it did to other readers).
🆕 New Journal Chapters
Substack, the newsletter platform I am using, keeps adding more features (and yet it still doesn’t support the basic code markdown ☠️). Now you have a fancy option to subscribe or navigate to a specific topic in my journal and ignore the rest. As of now, I have 6 different chapters:
Each chapter works as a separate newsletter. For example, if you are interested only in SQL, you can subscribe to SQL publications, and do not receive A/B test, ML, or Product Analytics articles. If you are subscribed to the Data Analysis Journal (as you are now), you will receive every newsletter.
🔥 Popular publications from Data Analysis Journal:
Read more - Data Analysis Journal - Product Analysis
A/B One-Pager (initial checklist)
A/B Test Checklist (updated checklist)
Read more - A/B Testing
Read more - Data Analysis Journal - Python
A new SQL function - QUALIFY! And How To Optimize A Query Run Time
Joining two tables that are not related by a foreign key relationship
Read more - Data Analysis Journal - SQL
Data Science and Statistics
Supervised machine learning — Binary logistic regression overview
Supervised Machine Learning — An Introduction To Support Vector Machines
Supervised Machine Learning - The Decision Tree Classifier Intro
Read more - Data Analysis Journal - ML
Brian Balfour - Learn Your Domain and Differentiate Yourself
Read more - Data Analysis Journal - Expert Insights
Before I go skiing and celebrate life, here’s one last thing from my favorite source - 2021: A Year In Charts. The whole 2021 in 25 charts. Here’s a similar one from McKinsey - 2021: The year in charts. Enjoy!
Hope you have a great end of the year ☃️. I will be away for the next 2 weeks, but then back every Wednesday, as always!
See you in January!