Digital Skills Development

Industry 4.0 spans a staggering array of topics, technologies, and domains that require both technical and business skills. Its complexity arises from the interplay and convergence of these diverse disciplines that need to come together to fundamentally transform the way a company operates and provides value to customers.  There isn’t anyone (company or person) who knows it all or can do it all – it requires a full ecosystem to come together. True leaders in the field are the ones who can navigate this uncharted territory by asking the right questions. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞𝐬 𝐨𝐟 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐞𝐯𝐞𝐫𝐲 𝐜𝐨𝐦𝐩𝐚𝐧𝐲 𝐬𝐡𝐨𝐮𝐥𝐝 𝐡𝐚𝐯𝐞 𝐚𝐧𝐬𝐰𝐞𝐫𝐬 𝐭𝐨: • What does your company look like in the era of Industry 4.0? What changes? • What are the skills and talents required to transform your company? • How is your company staying current with the latest technologies? Trends? And success stories? • What happens if you don’t do anything? • What is currently holding you back from transforming? • How will you manage resistance to change, both culturally and operationally, to ensure a smooth transition? • How is your company formalizing and embracing innovation? • What is your plan to integrate or phase out your existing legacy systems with new digital platforms without disrupting your current operations? • How do you safeguard our manufacturing processes, intellectual property, and customer data against cyber threats? • How will you measure the return on investment (ROI) for your digital transformation initiatives, especially when benefits might be intangible or long-term? • How will your digital transformation efforts enhance the customer experience, and how will you measure this impact? • As your operations grow and technology evolves, how do you ensure that your digital infrastructure and tools can scale accordingly? • How do you choose the right technology partners, ensuring they align with your goals, values, and long-term vision? • How are you leveraging digital tools to monitor, manage, and reduce your environmental footprint, and how does this factor into your broader digital transformation strategy? 𝐌𝐨𝐫𝐞 𝐢𝐧𝐟𝐨 𝐚𝐧𝐝 𝐞𝐱𝐚𝐦𝐩𝐥𝐞 𝐚𝐧𝐬𝐰𝐞𝐫𝐬 𝐡𝐞𝐫𝐞: https://lnkd.in/ex_qMx53 ******************************************* • Visit www.jeffwinterinsights.com for access to all my content and to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

If I had to start from scratch to become a Data Analyst in 2025, here's exactly what I’d do: (A roadmap I wish I had when I began 👇) 1. 𝐋𝐞𝐚𝐫��� 𝐂𝐨𝐫𝐞 𝐌𝐚𝐭𝐡 & 𝐒𝐭𝐚𝐭𝐬 Start with Descriptive Stats, Probability, Hypothesis Testing, Linear Algebra & basic Calculus. → These form the backbone of data intuition. 2. 𝐌𝐚𝐬𝐭𝐞𝐫 𝐏𝐲𝐭𝐡𝐨𝐧 + 𝐒𝐐𝐋 • Python: Pandas, NumPy, Matplotlib • SQL: Joins, subqueries, indexing, Window Functions, optimization → These are your bread-and-butter tools. 3. 𝐃𝐚𝐭𝐚 𝐖𝐫𝐚𝐧𝐠𝐥𝐢𝐧𝐠 Learn how to clean, transform, and merge messy data. → 70% of your job is here; don’t skip it. 4. 𝐃𝐚𝐭𝐚 𝐕𝐢𝐬𝐮𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 Use Tableau, Power BI, Seaborn, Plotly → Telling stories with data gets you noticed. 5. 𝐈𝐧𝐭𝐫𝐨 𝐭𝐨 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 Know the basics: Regression, Clustering, Model Evaluation → So you can support predictive use cases too. 6. 𝐁𝐮𝐢𝐥𝐝 𝐒𝐨𝐟𝐭 𝐒𝐤𝐢𝐥𝐥𝐬 Storytelling, communication, and structured thinking → This is what makes you irreplaceable. ♻️ Save this roadmap. Follow it step-by-step. And turn your data dreams into a real analytics career! 𝐏.𝐒. I share job search tips and insights on data analytics & data science in my free newsletter. Join 14,000+ readers here → https://lnkd.in/dUfe4Ac6

🚀 Now publicly available 🚀 The Data Innovation Toolkit! And Repository! (✍️ coauthored with Maria Claudia Bodino, Nathan da Silva Carvalho, Marcelo Cogo, and Arianna Dafne Fini Storchi, and commissioned by the Digital Innovation Lab (iLab) of DG DIGIT at the European Commission) 👉 Despite the growing awareness about the value of data to address societal issues, the excitement around AI, and the potential for transformative insights, many organizations struggle to translate data into actionable strategies and meaningful innovations. 🔹 How can those working in the public interest better leverage data for the public good? 🔹 What practical resources can help navigate data innovation challenges? To bridge these gaps, we developed a practical and easy-to-use toolkit designed to support decision makers and public leaders managing data-driven initiatives. 🛠️ What’s inside the first version of the Digital Innovation Toolkit (105 pages)? 👉A repository of educational materials and best practices from the public sector, academia, NGOs, and think tanks. 👉 Practical resources to enhance data innovation efforts, including: ✅Checklists to ensure key aspects of data initiatives are properly assessed. ✅Interactive exercises to engage teams and build essential data skills. ✅Canvas models for structured planning and brainstorming. ✅Workshop templates to facilitate collaboration, ideation, and problem-solving. 🔍 How was the toolkit developed? 📚 Repository: Curated literature review and a user-friendly interface for easy access. 🎤 Interviews & Workshops: Direct engagement with public sector professionals to refine relevance. 🚀 Minimum Viable Product (MVP): Iterative development of an initial set of tools. 🧪 Usability Tests & Pilots: Ensuring functionality and user-friendliness. This is just the beginning! We’re excited to continue refining and expanding this toolkit to support data innovation across public administrations. 🔗 Check it out and let us know your thoughts: 💻 Data Innovation Toolkit: https://lnkd.in/e68kqmZn 💻 Data Innovation Repository: https://lnkd.in/eU-vZqdC #DataInnovation #PublicSector #DigitalTransformation #OpenData #AIforGood #GovTech #DataForPublicGood

Today we unveil our inaugural list of Skills on the Rise in Human Resources, a data-backed ranking of the 10 fastest-growing skills that HR professionals should be investing in to get ahead in today’s world of work. Employee Communications tops the list, highlighting the importance of clear, effective internal communication as companies lead their employees through workplace changes. That’s followed by AI Literacy (No. 2) — suggesting that effective knowledge and use of AI tools can help HR professionals get ahead. To compile the list, we looked at unique LinkedIn data to reveal the HR skills that professionals are increasingly adding and that companies are increasingly hiring for. Check out the full list of Skills on the Rise in the U.S. and our methodology here: https://lnkd.in/SkillsontheRise25US. Which skills stand out to you on the list? And what other HR skills do you see rising in demand right now? Tell us in the comments. #SkillsOnTheRise

By 2030, these 11 abilities will decide who gets hired Most don’t show up on resumes yet. The World Economic Forum just revealed the top skills for 2030 in the Future of Jobs Report 2025. And it’s a wake-up call. Today's celebrated tech skills? AI will do those better by 2026. Those certifications? Outdated in 18 months. But here's the good news: The skills that matter most in 2030? Technology can't replace them. Start mastering these skills to stay relevant and be recognized: 1. AI and Big Data 🤖 ❌ Passively watch AI replace jobs ✅ Make AI your competitive edge → Use AI to automate weekly reports → Build self-updating dashboards and summaries 2. Analytical Thinking 🧠 ❌ Drown in opinions and noise ✅ Let data drive key decisions → Identify root causes before reacting → Monitor metrics that reveal blind spots 3. Resilience, Flexibility and Agility 🐆 ❌ Break down under shifting priorities ✅ Adapt fast and lead through change → Stay steady during messy execution → Pause, breathe, ask: “What’s the next best move now?” 4. Motivation and Self-Awareness 👤 ❌ Burn out chasing urgency ✅ Work in sync with your energy → Track your energy every 3 hours for a week → Schedule focus work when your mind feels sharp 5. Curiosity and Lifelong Learning 🔍 ❌ Stick to your job description ✅ Learn a complementary skill to your role → If you're in marketing, study basic product design → If you're in finance, explore storytelling with data 6. Leadership and Social Influence 🌟 ❌ Rely on your title for respect ✅ Build trust by how you think, speak and act → Explain why you made a tough call, not just what you decided → Share a client insight that helped your team level up 7. Technological Literacy 💻 ❌ Run to the IT helpdesk for every issue ✅ Build and adapt your own stack → Automate one repetitive workflow today using AI → Use familiar tools more efficiently (Excel, Slack) 8. Systems Thinking 🔧 ❌ React to broken processes ✅ Design workflows that scale → Improve one repeated but inefficient process this week → Ask: “Can this run without me?” 9. Empathy and Active Listening 🎧 ❌ Talk to be heard ✅ Listen to support, inspire and lead → Listen without needing to speak more in 1:1s → Decode what’s really being said 10. Creative Thinking 🎨 ❌ Wait for inspiration ✅ Build innovation into routine → Ask: “What’s another way to solve this?” → Try a small change to test a new idea 11. Talent Management 👥 ❌ Try to do it all ✅ Delegate and develop future leaders → List 3 tasks to delegate now → Improve hiring processes to onboard the right talent 💡 It’s not about doing more. It’s about evolving how you think, lead, and grow. Because the future expects you to. Which one are you focusing on this month? -- ♻ Share this with someone you’d want on your 2030 team. ➕ Follow me (Meera Remani) for future-ready leadership strategies. 🔔 My best insights for transforming your leadership career? Join my exclusive email list. Link below.

As GenAI becomes more ubiquitous, research alarmingly shows that women are using these tools at lower rates than men across nearly all regions, sectors, and occupations.   A recent paper from researchers at Harvard Business School, Berkeley, and Stanford synthesizes data from 18 studies covering more than 140k individuals worldwide.   Their findings:   • Women are approximately 22% less likely than men to use GenAI tools • Even when controlling for occupation, age, field of study, and location, the gender gap remains • Web traffic analysis shows women represent only 42% of ChatGPT users and 31% of Claude users   Factors Contributing the to Gap:   - Lack of AI Literacy: Multiple studies showed women reporting significantly lower familiarity with and knowledge about generative AI tools as the largest gender gap driver. - Lack of Training & Confidence: Women have lower confidence in their ability to effectively use AI tools and more likely to report needing training before they can benefit from generative AI.   - Ethical Concerns & Fears of Judgement: Women are more likely to perceive AI usage as unethical or equivalent to cheating, particularly in educational or assignment contexts. They’re also more concerned about being judged unfairly for using these tools.   The Potential Impacts: - Widening Pay & Opportunity Gap: Considerably lower AI adoption by women creates further risk of them falling behind their male counterparts, ultimately widening the gender gap in pay and job opportunities. - Self-Reinforcing Bias: AI systems trained primarily on male-generated data may evolve to serve women's needs poorly, creating a feedback loop that widens existing gender disparities in technology development and adoption.   As educators and AI literacy advocates, we face an urgent responsibility to close this gap and simply improving access is not enough. We need targeted AI literacy training programs, organizations committed to developing more ethical GenAI, and safe and supportive communities like our Women in AI + Education to help bridge this expanding digital divide.   Link to the full study in the comments. And a link also to learn more or join our Women in AI + Education Community. AI for Education #Equity #GenAI #Ailiteracy #womeninAI

No excuses today. Want to learn digital forensics but don’t know where to start? You don’t need to master everything at once and frankly, you never will and that’s OK! Even one actionable learning task a day compounds into real skill—while procrastinating over “someday” big courses leaves you stuck. Think of it this way: • 15 minutes a day = 91 hours a year • 30 minutes a day = 182 hours a year • 1 hour a day = 365 hours a year That’s the difference between waiting for a big break and building your expertise steadily. Here are free resources you can start with right now: 🔹 DigitalCorpora.org A library of disk images, memory dumps, and network captures used in forensic education and research. Everything here is free to download and legal to practice on. https://lnkd.in/d6WS5tye 🔹 Magnet Forensics CTF Shoutout to Jessica H. and Magnet Forensics. Download the challenge images and test yourself with any tools you have. No certificates here—just sharper skills. Chad Gish Jeff Rutherford Brandon Epstein https://lnkd.in/dT5-v6un 🔹 copy.sh/v86 A browser-based emulator that spins up dozens of systems—Unix, Linux, BSD, Windows, and more. Modern platforms are built on these. To understand the present, study the history. https://copy.sh/v86/ No lab? No problem. Run these in a VM, or use an old laptop. The point isn’t perfection—it’s practice. #forensics #breakitandfixit

I rebuilt the 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 Roadmap for 𝟮𝟬𝟮𝟲! It shows you what to learn before getting hired, how to get hired, and how to grow after you’re in the role from Junior Data Analyst to Senior and Lead. The 𝘃𝗶𝗱𝗲𝗼 is live, and the 𝗳𝘂𝗹𝗹 𝗿𝗼𝗮𝗱𝗺𝗮𝗽 is available as a Notion template. #𝟬 𝗘𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗶𝗼𝗻 • Understand the Data Analyst role • Compare data roles • Make a clear career decision #𝟭 𝗖𝗼𝗿𝗲 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗦𝗸𝗶𝗹𝗹𝘀 • Data & analytics terminology • SQL • Power BI or Tableau • EDA project • Dashboard project #𝟮 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗦𝗸𝗶𝗹𝗹𝘀 • Statistics (focus on interpretation) • Communication and storytelling • Analytical thinking and problem solving • Data modeling and metrics design #𝟯 𝗦𝘁𝗮𝗻𝗱 𝗢𝘂𝘁 • Python for analytics (Pandas, NumPy, Plotly) • Databricks for data analytics • AI prompt engineering • AI models at a high level #𝟰 𝗚𝗲𝘁 𝗛𝗶𝗿𝗲𝗱 • Build a clean portfolio • Improve and learn from projects • Optimize LinkedIn profile • Build a focused resume • Start applying for jobs • Optional certification #𝟱 𝗝𝘂𝗻𝗶𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 • Understand the business and stakeholders • Explore and understand data (EDA) • Maintain and improve existing reports • Build domain knowledge #𝟲 𝗦𝗲𝗻𝗶𝗼𝗿 / 𝗟𝗲𝗮𝗱 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 • Advanced data modeling • Mentor juniors and review work • Think beyond tasks and focus on impact • System-level analytics architecture

As we reach the midpoint of 2026, one thing has become increasingly clear: the conversation around AI has shifted. Again.    A year ago, much of the discussion centered on what's possible. Today, the focus is on what's practical: how we build the data foundations, governance, infrastructure, and workforce capabilities needed to create lasting value.    A few key learnings we're applying as we head into the second half of the year:  --AI transformation is ultimately a people transformation. Technology is advancing quickly, but realizing its potential means building a workforce that knows how to use it thoughtfully.  --AI fluency is a core capability. That means thoughtfully redesigning roles and workflows and giving employees the confidence to incorporate AI into their daily work while maintaining human judgment and accountability.  --The role of technology leaders is no longer focused only on delivering systems. We're helping shape enterprise strategy, building workforce capabilities, and creating the conditions for innovation to scale responsibly.    The pace of change isn't slowing down, but some principles remain constant: start with the problem you're trying to solve, invest in your people as much as your platforms, build governance from the beginning, and remember that every technology decision should ultimately create value for the people we serve.

I once interviewed for a security position, and something in that experience stuck with me. The interview was going well, good conversation, solid answers. Then, at one point, the interviewer mentioned some of my past engagements: • My community involvement • Papers I had written • Industry contributions • Speaking engagements It was clear they had looked me up before the interview. This wasn’t just about skills or certifications. It was about who I was beyond my CV. And that’s when it hit me: your online footprint matters, especially in cybersecurity. Companies hiring for security roles aren’t just looking for technical skills. They want someone who: ✅ Represents the company well (you are an extension of their security brand) ✅ Has no questionable online activity that could put their reputation at risk ✅ Is engaged in the cybersecurity community (because security is a constantly evolving field) Cybersecurity is a delicate field, trust is a big factor. If you’re in the space (or trying to break in), be mindful of: 🔹 Your online presence – What do your posts, comments, and interactions say about you? (This is not just about LinkedIn, other public social media as well) 🔹 Your reputation in the community – Are you contributing, learning, and growing? 🔹 Your professionalism – Employers will check more than just your resume. 💡 The lesson? People are watching, sometimes in ways you don’t expect. Make sure your digital footprint tells the right story. #Cybersecurity #CybersecurityCareerGrowth