Hi Reader, Most people think "personal brand" means LinkedIn, YouTube, TikTok.It doesn’t. In fact, every one of us has a personal brand. Inside your company for example, there are people who: trust you on certain topics come to you for advice see you as the “go-to” for some things That’s your brand. The real question is:→ are you shaping it intentionally, or leaving it to chance? When Miquel asked me how to build a personal brand, I broke it down into 4 simple questions: What’s your goal? Who...
7 days ago • 1 min read
Hi Reader, People think doing more = faster growth.It doesn't.In fact – in many cases it's the opposite.Recently I recorded a mentoring session with Sherin, a Data Analyst at Booking.com.She felt stuck at Level 2 and wasn’t sure how to grow. So I asked her what she works on.She said: “Everything. Finance, sales, marketing…” That’s the problem. When you spread yourself across too many domains: you never go deep enough you never build real context and expertise you never become the go-person...
14 days ago • 1 min read
Hi Reader, Most data professionals think they’re doing a good job. They deliver what’s asked.They answer questions.They build dashboards. And that’s exactly the problem.They’ve become order takers. This used to be “fine”.Today? It's very risky. Because order takers: Don’t get promoted Don’t get recognition Are the easiest to replace (by AI or by someone cheaper) The people who grow fast do something different.They lead. Not with authority.Not with title.But with how they think and how they...
20 days ago • 1 min read
Hi Reader, Most data professionals don’t manage their careers.They just… drift. From role to role. From opportunity to opportunity. And over time, that costs them years of growth. If I had to restart my data career today, I’d do 3 things differently: Pick a direction and stick to itMost people either don’t choose a direction… or keep changing it.Consistency compounds. Get mentors earlyI was lucky to have amazing mentors in my career. But I started way too late.Good mentoring compresses years...
28 days ago • 1 min read
Hi Reader, Most data teams are answering the wrong question.They ask "what happened?" when they should be asking "where is our best point of leverage?" Take any commerce business for example. At its core: Revenue = Units Sold * Price * Margin Want to grow revenue? You have three levers: Sell more Raise prices Improve margins Simple enough, except these variables pull against each other. Raise prices and you'll likely sell fewer units. Push volume and you may erode margin. The data...
about 1 month ago • 1 min read
Hi Reader, A few weeks ago I went flying with Enzo Blindow – VP of Data and AI at Prolific. I asked him: "If you could start your career all over again, what would you do differently?" His answer hit hard: "Don't just use cool technology for the sake of using it. Try to solve actual problems." Simple. But in a world overflowing with shiny technologies, that's exactly the reminder we all need. We also talked about: How to find problems actually worth solving Why Data and Analytics...
about 1 month ago • 1 min read
Hi Reader, Most people think career growth is about: The next role A bigger and better title Gaining more experience Learning a new skill or tool Very few people think about their career assets. Career assets are what compound. I define career assets as: Network: people you have access to Inventions: things you've built, written, created Frameworks: how you think and solve problems Brand: how you’re perceived when you're not in the room Our world is becoming more crowded, more competitive,...
about 2 months ago • 1 min read
Hi Reader, In a recent mentoring session I was asked: “Shachar, why did you leave your job at Meta?” I'll be honest. Leaving Meta was one of the toughest decisions I’ve ever made. In many ways, it was a dream job.Impact. Smart people. Stability. Compensation.A platform most people wouldn't voluntarily walk away from. Leaving meant giving up certainty.It meant starting from nothing – a freelancer with no brand, no product, no pipeline, and no guarantees. It wasn’t an easy journey to say the...
about 2 months ago • 1 min read
Hi Reader, Here’s a thought that might challenge how you see AI. I believe that what we are seeing isn't new.We’ve been here before: 1950s: people wrote assembly. You had to tell the machine exactly what to do, and how to do it 1970s: C arrived. Still low-level, still managing memory – but more abstract 1980s: C++. Object-oriented programming, closer to how humans think about systems 1990s: Python. In a few lines, you could do what once took thousands Every transition followed the same...
2 months ago • 1 min read
