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1.12 Chapter 1 quiz · TheNeuralNetwork

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Zero to Hired Data Engineer/01 What Is Data Engineering?

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What Is Data Engineering?

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1.1What a data engineer does1.2The data engineering lifecycle1.3Data generation: where data comes from1.4Upstream and downstream1.5Ingestion: moving data1.6Transformation: raw to useful1.7OLTP vs OLAP1.7.1OLTP: transactions and ACID1.7.2OLAP: analytical queries1.7.3Row vs column storage1.7.4OLAP operations: roll-up, drill-down, slice and dice1.7.5How OLTP and OLAP work together1.7.6Real systems and common myths1.8Normalization1.8.1Keys and functional dependencies1.8.21NF and 2NF1.8.33NF and BCNF1.8.44NF and 5NF1.8.5Finding keys: closure and Armstrong's axioms1.8.6Decomposition: lossless joins and dependency preservation1.8.7Worked example: an order table in SQL1.9Dimensional modeling: facts and dimensions1.10Storage: databases, warehouses, lakes and lakehouses1.11Putting it together: one order's journey1.12Chapter 1 quiz

next chapters

02Python Fundamentals

03SQL for Data Engineers

04Data Modeling & Warehousing

05Building ETL/ELT Pipelines

06Big Data with PySpark

07Orchestration with Airflow

08Cloud Data Platforms

09Streaming with Kafka

10Capstone & Interview Prep

01 What Is Data Engineering?/1.12 Chapter 1 quiz

§ 1.12section 25 of 25·~2 min

Chapter 1 quiz

Six short clips, one for each big idea in this chapter: the lifecycle, ingestion, upstream changes, OLTP and OLAP, normalization, and dimensional modeling.

Each clip plays once and stops on a question. Watch it, pick an answer, then read why. You can replay a clip as many times as you like. Press Next to start.

← previous1.11 Putting it together: one order's journey