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Data and Database Foundation

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Course Overview Print

This 1-day course provides a practical introduction to the foundational concepts of data and databases that support modern Data Engineering work. Participants will explore how data is structured, stored, related, queried, and governed, while gaining exposure to key topics such as relational databases, basic SQL, data quality, and responsible data handling. The course is designed to build confidence in learners who are new to data systems and to prepare them for further study in areas such as data pipelines, cloud data platforms, and analytics engineering.

Key Topics

  • Understand fundamental data and database concepts.
  • Explain relational database structures and relationships.
  • Recognize common data quality issues
  • Write basic SQL queries

Course Outline

Module 1: Introduction to Data Engineering Foundations

  • What Data Engineering is
  • Role of data engineers
  • Importance of strong data foundations
  • How data supports analytics and business decision-making

Module 2: Understanding Data

  • Data types and formats
  • Structured vs. semi-structured data
  • Common data sources
  • Data granularity
  • Data sensitivity and classification

Module 3: Relational Database Basics

  • Tables, rows, and columns
  • Primary keys and foreign keys
  • Database relationships
  • Constraints and data integrity
  • Basic Entity Relationship (ER) concepts

Module 4: SQL Fundamentals

  • Retrieving data using SELECT
  • Filtering data with WHERE
  • Sorting data with ORDER BY
  • Grouping data using GROUP BY
  • Aggregate functions (COUNT, SUM, AVG, etc.)
  • Simple table joins (JOIN)

Module 5: Data Modelling and Organisation

  • Organizing data effectively
  • Reducing data duplication
  • Basic normalization concepts
  • Structuring data for reliability and efficiency

Module 6: Data Quality and Metadata

  • Identifying missing values
  • Detecting duplicates
  • Handling invalid records
  • Managing inconsistent formats
  • Understanding metadata and data dictionaries

Module 7: Data Governance and Responsible Use

  • Data privacy considerations
  • Data security and access control
  • Data retention practices
  • Responsible data handling
  • PDPA-aware data management in Singapore

Module 8: Practical Mini-Exercise

Participants apply their learning by:

  • Classifying different data types
  • Creating a simple database model
  • Writing basic SQL queries
  • Identifying data quality and governance issues in a business scenario
*Important Note : Fees are subject to Singapore's prevailing Goods and Services Tax (GST).
Data and Database Foundation
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