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Showing posts from February, 2026

How to Get Data Analyst Job in 2026 – Complete Career Roadmap by GVT Academy

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Complete Career Roadmap by GVT Academy The demand for Data Analysts in 2026 is stronger than ever. Companies across IT, finance, healthcare, e-commerce, and startups are hiring skilled professionals who can turn raw data into meaningful insights. If you’re planning to start your career in analytics, this step-by-step guide from GVT Academy will help you understand exactly how to get a Data Analyst job in 2026 , even if you are a fresher or from a non-technical background. Why Data Analyst is One of the Best Career Options in 2026? The world runs on data. Every company today makes decisions based on numbers. That’s why: Data Analyst jobs are increasing rapidly in India and globally Freshers are getting entry-level analyst roles Salary packages are highly competitive Work-from-home and hybrid opportunities are available Career growth is strong (Data Analyst → Senior Analyst → Data Scientist → Business Analyst) In 2026, companies care less about your degree and more about what you can act...

Will AI Replace Data Analysts and Data Scientists? Let’s Be Honest

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GVT Academy This is one of the most common questions students ask today: “If AI can analyze data, write code, and build models… Do we still need Data Analysts and Data Scientists?” It’s a valid concern. But here’s the honest answer:  πŸ‘‰ AI will not replace Data Analysts and Data Scientists. πŸ‘‰ But professionals who don’t adapt to AI may get replaced. Let’s understand why. πŸ”Ž 1️⃣ AI Is a Tool — Not a Decision Maker AI can: Clean data Suggest models Generate insights Automate reports But AI cannot: Understand business goals deeply Ask the right analytical questions Interpret insights in business context Take accountability for decisions Data roles are not just about running tools — they are about thinking critically and solving real problems. 🧠 2️⃣ Companies Don’t Want Just Data — They Want Direction A dashboard means nothing without interpretation. For example: If sales drop by 15%, AI can show the number. But a Data Analyst must answer: Why did it happen? Which region is aff...