Data Analytics Explained: The 21 Most Important Concepts to Know
Lore So What
@loresowhatAbout
I’ll mentor you until you land a Data Job. 👉 Apply to my Academy: https://go.analyticsautomation.academy/FOljAM Ciao 👋 I’m Lore and I’m a Self-Taught Data Analytics Lead working at Amazon. My goal is to craft the ultimate learning resources to help you break into and thrive in the exciting world of Data Analytics and Data Science 🚀 While doing this, I will do my best to remove the fluff and answer the SO WHAT question 🤌 📩 Get in touch [email protected]
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Video Description
Join my Academy, learn Data & AI skills and land a job👇 https://analyticsautomation.academy/ On the surface, databases, data lakes, and warehouses seem similar, but oddly enough, knowing their differences can make or break your data career. In this video, I explain key data concepts like databases, data lakes, warehouses, and marts, plus essential analytics terms, coding languages, data processing, and reporting to help you ace interviews and excel in data roles. 📸 SOCIAL Instagram and TikTok - @Loresowhat https://www.instagram.com/loresowhat/ https://www.tiktok.com/@loresowhat 📩 Get in touch: [email protected] 🔎 CONTENT 0:00 Introduction to Data Concepts 2:11 Data Categories: Structured, Semi-structured, and Unstructured 4:59 Data Storage: Database, Data Lake, Data Warehouse, and Data Mart 8:21 SQL vs Python: Different Languages for Data 10:35 Data Processing: Data Modeling, Pipelines, ETL and ELT 16:06 Data Analysis Techniques: Descriptive and Inferential Statistics 20:51 Reporting and Visualization: KPIs, OKRs, and Metrics 24:19 Conclusion and Further Learning #DataAnalytics #DataScience #DataEngineering
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