This week’s issue was inspired by readers’ feedback and discourse on Reddit. Denise H. asked “There’s so many resources out there on starting a career in analytics. Skill advice videos from a few years ago are already obsolete. Do you think this will ever slow down?”.

This is a tricky, but important, question. One asked by many people considering a career in data (even those of us already working in data). Tricky, because there is no one-answer-fits-all. Important, because it is relevant to each and every data professional.

It can be unnerving, exhausting, even frustrating how quickly and often things change in any data field. Just a couple years ago it was gawked at to use AI written email correspondence whereas now it’s just about everywhere. But honestly, majority of the “changes” we see don’t make a direct impact as fast or big as you think. Once you’ve seen trends come and go, you start to see what skills really mattered all along.

Do I think the changes will slow down? Most likely, AI has caused a lot of excitement in the last few years, but the behavior of changing and innovating will probably never end – which I think can be a good thing.

There are many foundational skills that carry over from one tool/trend to the next. So in this issue I’ll share what some of those skills are, how to build on them, and why they’re not going out of style any time soon.

The world of data moves fast. One year it’s notebooks, the next it’s dbt, then AI-powered dashboards. Tools will come and go — some faster than others.

But what has never (and likely will never) change, are some soft skills that make up the mindset of an analyst.

Even the fastest and most efficient coder can stumble in a professional environment without developing these skills.

It’s about curiosity (“what’s really happening here?”), clarity (“how do I explain this plainly?”), and communication (“what does my audience need to know, not what can I show them?”).

Every time I’ve had to learn a new tool, these fundamentals have carried me through and set me apart from others. If you know how to frame the right question, explore the data logically, and communicate insights simply, you’ll adapt to any new method.

If you ever feel overwhelmed by the endless stream of “must-learn” tools, remember that it’s not about keeping up with every change. It’s about sharpening the skills that never lose value and applying them to whatever tools are beneficial at the time.

Why Soft Skills Still Matter in the Age of AI | Working Knowledge by Letian Zhang and Jay Fitzgerald, Harvard Business School
Zhang states that as AI automates more technical and repetitive tasks, soft skills (communication, critical thinking, etc.) become foundational. The authors found that many specialized skills depend on underlying general soft skills. Read more

So you want a career in data analytics? 4 must-haves from the pros by Talend Team
An article that captures what I believe every data professional has in common at their core. These are 4 foundational must haves when working with data. Read more

Although employers want tech expertise, ‘communication’ remains most in-demand skill, analysis shows by Carolyn Crist
Based on analysis of job postings, communication remains at or near the top of most demanded skills, even as specialized technical skills proliferate. Read more

iShortn #productivity
A neat tool I found kind of by accident. This app will allow you to create custom short links (think Bitly but back in the day before they started charging for everything). The developer, Kamoaba, is very engaged with the app and has made a very generous free version.

Relay.app #AI #productivity
Founded by ex product manager at Google (Jacob Bank). This AI agent builder makes task management a breeze. From scanning websites for research to automating tedious tasks Relay can handle it all. At the time of this issue anyone can get 500 AI credits and 200 steps complimentary each month.

▶️ Generate Excel Data with Chat GPT - Create Practice Datasets! by Cellmates
Creating or even searching for your own practice datasets can suck. This tutorial shows how to leverage ChatGPT to automatically generate structured Excel datasets, saving hours of manual data creation by specifying formats, columns, and record counts.

▶️ Data Analyst on How to Turn Business Metrics to Insights by Christine Jiang
Christine Jiang does an excellent job here showing how to break down relevant business questions and offers an framework to understanding metrics. A good video to watch for anyone wanting to enhance their business communication in analytics.

Did you know? The first website is still online. It was created in 1991 by Tim Berners-Lee and explains what the World Wide Web is.

What would you like to see next? At the end of each issue I like to open up the floor to everyone – if you have a suggestion for what you would like to see next please share it below in the comments, in the readers’ feedback survey, or email me directly at: [email protected]