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Database Management 1: Analysis

Ce cours n'est pas disponible en Français (France)

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Database Management 1: Analysis

Instructeur : 孔令傑 (Ling-Chieh Kung)

Inclus avec En savoir plus

6 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

1 semaine à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

6 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

1 semaine à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Design relational database schemas by using ER diagrams and ER-to-relational mapping to turn business rules into tables and keys.
Write SQL queries using PostgreSQL to retrieve, filter, join, aggregate, and manipulate data across relational databases.
Apply advanced SQL techniques including CTEs, Views, Window Functions, and User-Defined Functions to extract complex business insights.
Integrate SQL analysis with Python tools — comparing SQL and pandas, and using DuckDB to query DataFrames and files within a Python environment.

Détails à connaître

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Récemment mis à jour !

octobre 2026

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Il y a 6 modules dans ce cours

Learn SQL and Database Analysis From Scratch! Go from no database experience to writing advanced SQL queries and analyzing real-world data with PostgreSQL and Python. This course gives you the core knowledge and practical skills to understand, query, and analyze data in relational databases — with no prior background required.

You'll start by learning why organizations use database systems, how relational and NoSQL databases differ, and how databases fit into a standard system architecture. From there, you'll learn to model real-world business rules using Entity-Relationship (ER) diagrams, then convert those models into concrete relational schemas with tables, primary keys, and foreign keys. The core of the course is SQL programming, taught using PostgreSQL. You'll write queries to retrieve, filter, join, sort, and aggregate data — then progress to advanced techniques including nested queries, Common Table Expressions (CTEs), Views, Window Functions, and User-Defined Functions. These skills let you extract complex business insights directly from a database. The course closes by bridging SQL with general-purpose programming: you'll compare SQL with Python's pandas library, learn when to use each, and apply DuckDB to run SQL queries directly on DataFrames and CSV files within a Python environment. A real-world ambulance allocation case study ties analysis and visualization together. Who this is for: Aspiring data analysts, business analysts, developers, and anyone who works with data and wants to build practical, job-ready database and SQL skills from the ground up.

Discover why organizations rely on databases instead of traditional files like Excel. Explore how Database Management Systems solve problems like data redundancy, inconsistency, and concurrency. Compare Relational and NoSQL databases to understand when to use each. Examine system architecture through the Taiwan High Speed Rail (THSR) ticketing case study, and identify the professional roles that make up the database ecosystem.

Inclus

6 vidéos1 lecture1 devoir

Design a relational database from the ground up. Model business rules using entities, attributes, and relationships in the Entity-Relationship (ER) framework. Construct ER diagrams to visualize requirements for a retail business case study. Then convert your ER models into concrete relational schemas—complete with tables, primary keys, and foreign keys—using a systematic 7-step mapping algorithm.

Inclus

12 vidéos1 devoir

12 vidéosTotal 133 minutes

2-1 A motivating example13 minutes
2-2 Entities (1)11 minutes
2-3 Entities (2)9 minutes
2-4 Relationships (1)10 minutes
2-5 Relationships (2)9 minutes
2-6 Entity-relationship diagram (1)13 minutes
2-7 Entity-relationship diagram (2)6 minutes
2-8 ER models, relational models, and relational schema12 minutes
2-9 The ER-relational mapping (1)15 minutes
2-10 The ER-relational mapping (2)11 minutes
2-11 The ER-relational mapping (3)11 minutes
2-12 Summaries and remarks12 minutes

1 devoirTotal 30 minutes

W2 Quiz30 minutes

Write SQL to manage and analyze data in PostgreSQL. Create a Data Dictionary to document table structures, data types, and constraints. Build and modify tables using Data Definition Language (DDL) with referential integrity constraints. Construct queries to retrieve, filter, join, sort, and aggregate data for business insights. Insert, update, and delete records while maintaining data integrity.

Inclus

12 vidéos1 devoir

12 vidéosTotal 171 minutes

3-1 Basic SQL Programming: An Introduction14 minutes
3-2 The data and PostgreSQL installation17 minutes
3-3 Data types and constraints17 minutes
3-4 Referential triggers and table alternation17 minutes
3-5 Data dictionary8 minutes
3-6 Filtering, projection, and set operations (1)11 minutes
3-7 Filtering, projection, and set operations (2)10 minutes
3-8 Merging tables (1)16 minutes
3-9 Merging tables (2)17 minutes
3-10 Sorting and aggregation16 minutes
3-11 Dealing with complex data types13 minutes
3-12 Insertion, deletion, and updating in SQL15 minutes

1 devoirTotal 30 minutes

W3 Quiz30 minutes

Master advanced SQL techniques for deep data analysis. Construct nested queries, then refactor them for readability using Common Table Expressions (CTEs) and Views. Handle null values, implement conditional logic with CASE, and perform conditional aggregation with FILTER. Calculate rankings, running totals, and moving averages using window functions. Encapsulate reusable logic in User-Defined Functions (UDFs).

Inclus

13 vidéos1 devoir

13 vidéosTotal 133 minutes

4-1 Introduction3 minutes
4-2 Nested queries - With IN, ANY, and ALL17 minutes
4-3 Nested queries - With EXISTS9 minutes
4-4 Nested queries - With aliasing, and JOIN11 minutes
4-5 Flattening nested queries using CTE17 minutes
4-6 Flattening nested queries using Views (1)8 minutes
4-7 Flattening nested queries using Views (2)12 minutes
4-8 Null value manipulation9 minutes
4-9 If-else selection8 minutes
4-10 Conditional aggregation8 minutes
4-11 Window functions (1)9 minutes
4-12 Window functions (2)10 minutes
4-13 User-defined functions13 minutes

1 devoirTotal 30 minutes

W4 Quiz30 minutes

Connect SQL skills to general-purpose programming. Compare declarative (SQL) and imperative (Pandas) paradigms to understand when each excels. Query CSVs and DataFrames directly using DuckDB within Python. Apply your skills to a real-world ambulance allocation case study, combining SQL analysis with data visualization to generate actionable insights.

Inclus

10 vidéos1 devoir

10 vidéosTotal 138 minutes

5-1 Introduction3 minutes
5-2 Other data-processing tools14 minutes
5-3 Declarative vs. imperative programming17 minutes
5-4 DuckDB (1)18 minutes
5-5 DuckDB (2)16 minutes
5-6 Case study - Missions16 minutes
5-7 Case study - Data and Tasks13 minutes
5-8 Case study - Analysis (1)17 minutes
5-9 Case study - Analysis (2)17 minutes
5-10 Case study - More Tasks6 minutes

1 devoirTotal 30 minutes

W5 Quiz30 minutes

Consolidate your learning by reviewing key concepts: ER modeling, relational schema design, basic and advanced SQL techniques, and SQL-Python integration.

Inclus

2 vidéos1 devoir

Instructeur

孔令傑 (Ling-Chieh Kung)

National Taiwan University

10 Cours114 729 apprenants

Offert par

National Taiwan University

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Foire Aux Questions

No prior experience is needed. The course starts from the very beginning — explaining what a database is and why organizations use them — and builds progressively from foundational concepts to advanced SQL techniques. If you can use a computer and work with files, you have everything you need to start.

The primary tool is PostgreSQL, an industry-standard relational database system used for all SQL demonstrations and exercises. In the final module, you'll also work with Python, the pandas library, DuckDB, and Matplotlib as part of a real-world data analysis and visualization case study.

Most SQL tutorials stop at SELECT statements and basic JOINs. This course goes significantly further — covering advanced techniques like nested queries, Common Table Expressions, materialized Views, Window Functions for rankings and moving averages, and User-Defined Functions for reusable logic. It also covers relational data modeling using the ER model, giving you an understanding of how databases are designed from business requirements, not just how to query them.

This course builds foundational skills for roles including Data Analyst, Business Analyst, Database Administrator, and Backend Developer. SQL is one of the most consistently in-demand technical skills across industries, and the combination of relational modeling, advanced SQL, and Python integration covered here prepares you for real analytical work in any data-driven organization.

This is the first of three courses. Course 1 focuses on analysis — understanding, modeling, and querying databases. Course 2 covers architecture design, including schema normalization, transactions, concurrency control, and system implementation. Course 3 addresses efficiency optimization. Each course builds on the previous one, so completing this course prepares you fully for Course 2.

To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.