Data Lakehouse in Databricks: The Best of Both Worlds In today’s data-driven world, organizations are flooded with massive amounts of data—structured, semi-structured, and unstructured. Handling this variety of data and turning it into actionable insights is one of the biggest challenges in modern analytics. Traditionally, two primary approaches have been used: data lakes and data […]
🚀 Ultimate Data Career Roadmap 2026 – Choose Your Path in Data Are you planning to start a career in data in 2026? The data industry is booming, and there are multiple career options like Data Analyst, Data Engineer, Data Scientist, Machine Learning Engineer, and Data Architect. Each role has its own responsibilities, skills, and
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Unlocking Performance in PySpark: Lazy Evaluation Explained Introduction When working with big data using PySpark, performance is everything. One of PySpark’s most powerful (and often misunderstood) features is lazy evaluation. It’s not just a cool optimization trick—it’s the key to understanding how Spark executes your code efficiently. In this blog, we’ll break down what lazy
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Get Interview-Ready with the Ultimate Azure Data Factory Cookbook If you’re preparing for a Data Engineering interview and Azure is part of the tech stack, there’s one thing you can almost guarantee: You’ll be asked about Azure Data Factory (ADF). Whether it’s a product-based company, a startup, or a consulting giant — ADF has become
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Data engineering is a high-demand field, and certifications can help validate your expertise, boost your credibility, and open up career opportunities. Whether you’re looking to specialize in cloud platforms, big data processing, or real-time analytics, obtaining the right certification can set you apart from the competition. However, simply earning a certification isn’t enough—you need hands-on
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How to Learn Data Engineering in 2025: A Step-by-Step Guide Data engineering is one of the most in-demand skills in the tech industry. With the rapid growth of AI, machine learning, and big data, companies need skilled data engineers to manage, process, and analyze vast amounts of data efficiently. If you’re looking to start your
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