Data Engineers

𝟲 𝗙𝗥𝗘𝗘 𝗢𝗻𝗹𝗶𝗻𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗧𝗼 𝗖𝗵𝗮𝗻𝗴𝗲 𝗬𝗼𝘂𝗿 𝗖𝗮𝗿𝗲𝗲𝗿 𝗜𝗻 𝟮𝟬𝟮𝟱 😍 🎯 Want to switch careers or upgrade your skills — without spending a single rupee? Check out 6 handpicked, beginner-friendly courses in high-demand fields like Data Science, Web Development, Digital Marketing, Project Management, and more. 🚀 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/4e1I17a 💥 Start learning today and build the skills top companies want!✅️

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Tips to become a Data Engineer 👇👇 1. Data Engineering Basics: At its core, it's about efficiently moving and reshaping data from one place/format to another. 2. Be Curious: The field is vast. Dive deep, ask questions, and always be in the mode of learning and experimenting. 3. Master Data: Understand the intricacies of data types, where they originate, and how they're structured. 4. Programming: Grasping a language is crucial. If you're unsure, start with Python – it's versatile and widely used in the industry. 5. SQL: A timeless tool for querying databases. Mastering SQL will empower you to work with data across various platforms. 6. Command Line: Familiarizing yourself with command line operations can save a lot of time, especially for quick and repetitive tasks. 7. Know Computers: A basic understanding of how computers communicate and process information can guide better data engineering decisions. 8. Personal Projects: Practical experience is invaluable. Start projects, learn from them, and showcase your work on platforms like GitHub. 9. APIs and JSON: Many modern data sources are API-based. Understanding how to extract and manipulate JSON data will be a daily task. 10. Tools Mastery: Get proficient with your primary tools, but stay updated with emerging technologies and platforms. 11. Data Storage Basics: Know the difference and use-cases for Databases, Data Lakes, and Data Warehouses. Understand the distinction between OLTP (online transaction processing) and OLAP (online analytical processing). 12. Cloud Platforms: The cloud is the future. AWS, Azure, and GCP offer free tiers to start experimenting. 13. Business Acumen: A data engineer who understands business metrics and their implications can offer more value. 14. Data Grain: Dive deep into datasets to understand their finest level of detail. It aids in more precise querying and analytics. 15. Data Formats: Recognizing main data formats (like JSON, XML, CSV, SQLite, Database) will help you navigate different datasets with ease.

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ETL vs ELT – Explained Using Apple Juice analogy! 🍎🧃 We often hear about ETL and ELT in the data world — but how do they actually apply in tools like Excel and Power BI? Let’s break it down with a simple and relatable analogy 👇 ✅ ETL (Extract → Transform → Load) 🧃 First you make the juice, then you deliver it ➡️ Apples → Juice → Truck 🔹 In Power BI / Excel: You clean and transform the data in Power Query Then load the final data into your report or sheet 💡 That’s ETL – transformation happens before loading ✅ ELT (Extract → Load → Transform) 🍏 First you deliver the apples, and make juice later ➡️ Apples → Truck → Juice 🔹 In Power BI / Excel: You load raw data into your model or sheet Then transform it using DAX, formulas, or pivot tables 💡 That’s ELT – transformation happens after loading

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Kavitha's Journey to become a Data Engineer 👇👇 1. Startup to Dream Job Journey: - Started at a startup in India, transitioned to Infosys, then grabbed UK opportunity. - Shifted from legacy Mainframe to AWS Cloud, pursued Master's from illinoisstateu, and secured dream job at Statefarm. 2. Learn Fundamentals: - Assess skills, understand role. - Gain proficiency in Python, SQL. - Learn data technologies. 3. Database and Modeling Skills: - Understand databases, gain proficiency. - Learn data modeling principles. 4. Master ETL, Warehousing, and Visualization: - Understand ETL, data warehousing. - Gain experience in building warehouses. - Familiarize with visualization tools. - Got Certified as AWS Solutions Architect. 5. Utilize LinkedIn for Job Search: - Network and connect with professionals. - Showcase skills and achievements. - Utilize job search feature, leading to dream job at Statefarm. Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C

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Data Lake vs Data Warehouse

Kavitha's Journey to become a Data Engineer 👇👇 1. Startup to Dream Job Journey: - Started at a startup in India, transitioned to Infosys, then grabbed UK opportunity. - Shifted from legacy Mainframe to AWS Cloud, pursued Master's from illinoisstateu, and secured dream job at Statefarm. 2. Learn Fundamentals: - Assess skills, understand role. - Gain proficiency in Python, SQL. - Learn data technologies. 3. Database and Modeling Skills: - Understand databases, gain proficiency. - Learn data modeling principles. 4. Master ETL, Warehousing, and Visualization: - Understand ETL, data warehousing. - Gain experience in building warehouses. - Familiarize with visualization tools. - Got Certified as AWS Solutions Architect. 5. Utilize LinkedIn for Job Search: - Network and connect with professionals. - Showcase skills and achievements. - Utilize job search feature, leading to dream job at Statefarm. Data Engineering Interview Preparation Resources: https://whatsapp.com/channel/0029Vaovs0ZKbYMKXvKRYi3C

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