Data & AI Articles

Guides on the tools, the roles and the honest realities of working with data — including the parts other training providers leave out.

• Data Analytics — SQL, Power BI, Tableau and Excel guides
• Data Science — Python, machine learning and modelling
• Generative AI — how LLMs work and how to build with them
• Career & Jobs — role comparisons and hiring guidance

• What is Data Analytics? A Beginner's Guide — Data analytics is the practice of examining data to answer a question someone actually cares about. Here is what that means in practice, the four types of analysis, and what analysts really do all day.
• Excel vs Power BI vs Tableau: Which Should You Learn? — These three tools are compared constantly and they solve different problems. What each is genuinely good at, the point at which each breaks down, and which to learn first.
• Data Analyst vs Data Scientist: What's the Real Difference? — The two titles get used interchangeably and they are not the same job. The difference that actually holds up, how the daily work diverges, and which one to target first.
• Skills Required to Become a Data Analyst — Not the list of twenty skills you will find elsewhere. What data analyst hiring actually screens for, how deep to go in each, and what is safe to skip at the start.
• Data Science Roadmap for Beginners — A realistic ordered path into data science — what to learn, in what order, what to skip, and the specific mistakes that cost beginners months of wasted effort.
• What is Generative AI? Explained Simply — A clear explanation without the hype: how generative AI actually works, why it hallucinates, what it is genuinely good and bad at, and what it means for your career.