Lec#1 2

Welcome to Lecture 1 (Part 2) of the Data Analytics & Engineering Course! In this session, we take a deep dive into the core foundations of modern data architecture: how data originates, how it is classified, file format trade-offs, storage architectures, and end-to-end data pipeline designs (ETL vs. ELT). 📌 What You'll Learn in This Video: Data Origin & Types: Human-generated, machine-generated, transactional, and derived/calculated data. Data Classification: Structured, Semi-Structured (JSON/XML), and Unstructured formats. Data File Formats Compared: CSV, Excel, JSON, Parquet (Columnar), and Avro (Row-based) — why Parquet is king for analytics and Avro for streaming. Data Acquisition Strategies: APIs, Web Scraping, Direct DB Queries, Sensor/IoT telemetry, and Streaming. Storage Systems: Files, OLTP Databases, Data Warehouses (OLAP), Data Lakes, Delta Lakes, and Data Lakehouses. Data Pipelines & Processing: ETL vs. ELT architectures, Batch vs. Streaming vs. Hybrid workflows, and key pipeline stages (Ingestion, Transformation, Orchestration, Data Quality, Loading, and Monitoring). ⏱️ Timestamps: 00:00 - Introduction & How Data Originates (Human vs. Machine) 02:50 - Transactional & Derived Data 05:20 - Structured, Semi-Structured & Unstructured Data 11:00 - JSON & Semi-Structured Data Parsing 16:05 - Data File Formats (CSV vs. Excel vs. JSON vs. Parquet vs. Avro) 23:43 - Parquet Deep Dive (Columnar Storage & Predicate Pushdown) 34:07 - Data Acquisition Methods (APIs, Scraping, IoT & Streams) 48:15 - Data Storage Evolution (OLTP, OLAP, Data Lake, Delta Lake, Lakehouse) 01:02:11 - Data Pipelines: ETL vs. ELT Architectures 01:14:38 - Batch vs. Streaming vs. Hybrid Processing 01:25:56 - Storage Tiers (Hot/Cache vs. Cold/Archive) & Data Architecture 01:37:00 - Core Stages of a Data Pipeline (Ingestion to Monitoring) 🔔 Subscribe & Stay Connected: Don't forget to Like, Subscribe, and hit the Bell Icon to keep up with the full series! Share your thoughts and answers to the in-lecture questions in the comments below. #DataEngineering #DataAnalytics #ETL #ELT #DataLakehouse #Parquet #SQL #Python