Sonek Data School’s Post

Imagine a scientist👩🔬 examining two data points - one from behavioral data, the other from claimed data. Your gut reaction might be "Why are they different?"❓- a question that sparks much intrigue. Recently, a client and I 👥 dove into this very mystery during a project debrief. She was convinced we'd be bewildered, possibly even disheartened 😞 by the contrast. Ironically, this dichotomy is something we consistently encounter. Why does this happen? It's not that people intentionally deceive us, rather it's a consequence of differing cognitive processes at play. Picture this - you're in a store 🏬, you take a minute to select a detergent. Later, you’re faced with answering ten questions about the same detergent. Your brain's processing mode during these two instances will be drastically different. The trick lies in understanding this and knowing how to harness it. Whether you're gathering data to boost product sales or collecting insights for an essay, remember - it's not just the data, but the context that counts 🎯. Care to step into the world of nuanced data interpretation with us? 🌍

As a data scientist, time is my most valuable resource. And I’ve learned one crucial truth: Most productivity methods work if...... YOU STICK WITH THEM LONG ENOUGH. When you commit to a single method, here’s what happens: 1. You build discipline – The secret is in sticking to one method for at least 30 days. That’s how long it takes to turn it into a habit. 2. You manage distractions better – By staying consistent, you’ll notice fewer distractions, allowing you to focus more on deep work. 3. You create real results – Once a method becomes a habit, the results will follow. You won’t need to hop from one tool to the next. Is it easy? Not always. But is it worth it? Absolutely. For example, one of my favorite experiments was using a children’s alarm clock to create urgency in my day. It helped me focus and push through tasks, especially when deadlines seemed far away. Next time you try a new productivity hack, give it a real shot—stick with it for 30 days. You might just surprise yourself with the results. ____ Want to learn about 3 Weekly Questions to Land Your Next Data Science Promotion (Without Burning Out)? I shared it on my newsletter (Link in the comments). And follow Penelope Lafeuille for more on Data Scientist Stuffs + Health + Tech

What I see increasingly in my feed is "View my verified achievement from [platform X]." What I see less and less is "Here's a cool data project of mine, where [your craziest or stupidest idea]." This is how you gain experience. I'm not saying theory isn't important—quite the opposite. But you have to apply what you learn; otherwise, what's the point?! Stop scrolling. Stop reading about the same data tools. Stop clicking through that one extra online course. Start today. Take action. Build something useful (even if it's useless to 99% of people). Here's a quick reminder on how to know you're on the right path: If you stumble upon something and scratch your head trying to solve it—know—you're on the right path. Takeaway: Build cool things & don't be boring!

#ConnectedCustomerRelationships and understanding #DataScience are crucial for aspiring business leaders and students today. We need both business experts to develop analytical skills 📊 and data scientists to build business acumen 💼 to communicate and solve complex problems🙌. This revelation must be implemented by shifting the mindset 🤔, enhancing technical training 🧑💻, building capability 💪, and encouraging cross-functional team discussions 🗣️ to ensure proper communication and knowledge sharing 💡in the workplace. Relying on data scientists alone to solve the problems doesn’t get the desired results, and the mistakes can be too costly to handle! We need an integrated approach🤝 Inspired by learnings from the audited course Professional Certificate in #StrategicManagement by Wharton Online on #Edx and the book Connected Strategy by Professor Dr. Nicolaj Siggelkow and Professor Dr. Christian Terwiesch #ProblemSolving #BusinessStrategy #DataDrivenLeadership #FutureOfWork #DigitalTransformation #EmpatheticLeadership #BeingGeneralistIsPowerful

An actionable, practical tool by the Massachusetts Institute of Technology for marketing teams provides a structured template to think through problems and solve them by leveraging data 📊🙌 Check out the framework here: https://bit.ly/3rO5GSq It’s a great example of how an integrated approach, combining business acumen and data science, can work together to enhance customer experience✨🌟 MIT Sloan Management Review #CustomerExperience #DataAnalytics #MarketingTools #BusinessStrategy #ProblemSolving #BeingGeneralistIsPowerful

Interesting article from #HBR! Communicating data science results effectively to decision-makers is a delicate balance. Oversimplification risks trivializing the work, while complexity can hinder understanding. #dataScience #decisions #business

Good morning! Fun fact! Analysis isn’t just for data nerds (although I’m massively guilty of this), it’s something we all do daily. For me personally, it has been essential in navigating the social world we live in. I’m not always the best at reading social situations and emotionally charged events triggers Flight Mode. Upon reflection, I even feel that I miss out on opportunities or standard social “things” simply because I don’t always recognise social cues until months down the line. Inquisitiveness is a beautiful part of life. We analyse situations, people, conversations, sometimes without even realising it. If you’re anything like me, you might have even practiced interactions based on past experience, or indeed who we feel we want to be in any given situation. How often do we stop and think—are we overcomplicating it? When does healthy curiosity turn into unnecessary noise? I’ve been reflecting on how much time I spend analysing things that might not need it (I’ve been know to spend over an hour debating pizza toppings, packets of crisps or, crikey, don’t give me a food menu!). Panic ordering is a regular occurance… Does anyone else find themselves caught up in the same habit? Would love to hear your thoughts on where you draw the line in your personal or professional life. JoGi P.S. apologies in advance for any pizza cravings caused… Hmm, that thin and crispy base…

This article beautifully explains how to bridge the gap between technical excellence and business outcomes by focusing on the ‘why’ behind the work. It highlights the importance of building trust, simplifying complex insights, and aligning data science efforts with meaningful business impact. What are your thoughts on achieving this balance?

👋 Data Scientists After a recent build, here's our learnings to help place yourself in the Top 3% of candidates: Key Takeaway: 𝐓𝐡𝐞𝐫𝐞 𝐢𝐬 𝐚 𝐬𝐢𝐠𝐧𝐢𝐟𝐢𝐜𝐚𝐧𝐭 𝐠𝐚𝐩 𝐢𝐧 𝐬𝐤𝐢𝐥𝐥𝐞𝐝 𝐩𝐫𝐨𝐛𝐥𝐞𝐦 𝐬𝐨𝐥𝐯𝐞𝐫𝐬 𝐰𝐢𝐭𝐡 𝐬𝐭𝐫𝐨𝐧𝐠 𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥 𝐭𝐡𝐢𝐧𝐤𝐢𝐧𝐠. Come equipped with: 💡 An understanding of the reasons behind solutions 💡 Knowledge about the deployment of solutions 💡 Awareness of how success is measured 💡 Recognition of the business value of solutions 💡 Basic theoretical knowledge of the models Talking Point: there’s still confusion around concepts like Gradient Boosting regularization and why overfitting occurs. How to stand out: 1️⃣ Address problems from beginning to end 2️⃣ Understand the theory behind your methods 3️⃣ Have a comprehensive grasp of what you are doing

Data is the lifeblood of decision-making. Those who can harness its power are in high demand. . Yes, you’ll need to notch skills in programming languages, machine learning and data visualisation. Equally important to your future employers are the critical soft skills you will develop in this program. . We’re talking about strategic thinking, effective communication, collaboration, and creative problem-solving. . These are the traits that make data professionals not just analysts but leaders and innovators in their fields. . Stand out with a data science qualification that is designed to make you indispensable in tomorrow’s workforce. FIND OUT MORE AT OUR WEBINAR THIS TUESDAY https://ow.ly/knov50TO7AY