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🔺 Azure Databricks in 60 Days for Data Scientists, Engineers, and Analysts
đź“ŤThe 60-Day Learning Objective
→ Hands-on Databricks workflows
→ Data pipeline Automation/Engineering
→ Performance tuning & cost-saving tricks
→ Machine learning & real-time analytics
→ Governance & security best practices
📍 Day 1: Databricks is Everywhere – Should You Care?
Databricks isn’t just a buzzword—it’s revolutionizing data engineering, data science, and analytics.
If you work with big data, streaming, or machine learning, Databricks is the platform you need to know.
đź“Ť Why Databricks?
→ Built on Apache Spark – Forget slow SQL queries. Spark distributes processing across multiple machines, speeding up your work.
→ Cloud-Native – Works seamlessly across Azure, AWS, and GCP.
→ Unified Data Workflows – Manage ETL, analytics, and ML in one platform.
→ Cost-Effective – Pay only for the compute you use, optimizing your budget.
📍 If you’re serious about handling big data and analytics, you can’t afford to ignore Databricks.LinkedIn
