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🔺 Azure Databricks in 60 Days for Data Scientists, Engineers, and Analysts
📍The 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.
📍 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
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🔺 How to Transition into Data Engineering Using Real Azure & Databricks Project
·ÇevrimiçiÇevrimiçi🔺From SQL to Data Engineering: What It Actually Takes (Live Session)
Thinking about transitioning into Data Engineering… but not sure where to start?
Most people:
Learn tools
Watch tutorials
Build small projectsBut still struggle to answer:
👉 “Can you design and build a real data pipeline?”
📍In This Live Session, I’ll Walk You Through:
What companies actually expect from Data Engineers
A real end-to-end pipeline (Bronze → Silver → Gold) built using Databricks & Azure
The gap between “learning” and “getting hired”
Common mistakes that slow people down
📍Who This Is For:
SQL Analysts looking to move into Data Engineering
Data professionals stuck at the “learning stage”
Anyone curious about Databricks, PySpark, and cloud pipelines
📍What You’ll Leave With:
A clear roadmap to transition into Data Engineering
Understanding of what real-world projects look like
Whether this path is right for you
👩🏽💻 About the Host
Hosted by Joy Onuoha, a Data Professional specialising in:
Databricks & PySpark
Azure Data Engineering
End-to-end pipeline developmenthttps://www.linkedin.com/in/joy-onuoha-ebedo-221aa0172?
📩 Next Steps
At the end of the session, I’ll share how you can build this type of project step-by-step with guidance — if you decide it’s the right fit.
(No pressure — this session is designed to give you clarity first.)
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