Big Data and AI

  By now, you’ve mastered the foundations of SQL—from basic queries to table design. In this final module, we’ll dive into three advanced pillars that elevate your database skills: Views, Stored Procedures, and Functions Transactions and Concurrency Performance Tuning & Best Practices These topics empower you to encapsulate logic, ensure data integrity under load, and optimize queries for real-world workloads. Views, Stored Procedures, and Functions Encapsulating complex logic in the database makes your applications cleaner and more maintainable. Views A view is a virtual table defined by a SQL query. Use views to: Simplify joins and aggregations into a single, reusable object Enforce data security by exposing only selected columns Provide backward compatibility when underlying schemas change Example: sql CREATE VIEW sales_summary AS SELECT product_id, DATE_TRUNC('month', sale_date) AS sale_month, SUM(quantity * price) AS total_revenue FROM sales GROUP BY product_id,...

  Chapter 12: Keys and Indexes Designing a robust schema goes beyond defining tables and columns. The right keys and indexes enforce data integrity, prevent anomalies, and turbocharge query performance. In this chapter, you’ll learn how to: Distinguish and implement primary keys and surrogate keys Configure foreign keys to uphold referential integrity Create the most effective indexes for your queries Balance speed gains against storage and maintenance costs By the end, you’ll know how to architect schemas that both safeguard your data and serve queries at lightning speed. 1. Primary Keys and Surrogate Keys A table’s primary key uniquely identifies each row. Choosing the right key type sets the foundation for joins, lookups, and integrity. 1.1 Natural vs. Surrogate Keys Natural Key An existing attribute or set of attributes that uniquely describes the entity (e.g., a country’s ISO code, a user’s email). • Pros: No extra column needed; human-readable. • Cons: Subject to business-...

  Part V: Designing Your Schema Chapter 11: Creating and Altering Tables Building a robust database schema starts with thoughtfully created tables and evolves with carefully applied modifications. In this chapter, you’ll learn how to: Define tables using CREATE TABLE Choose appropriate data types and sizes for each column Enforce data-quality rules through constraints ( NOT NULL , UNIQUE , CHECK ) Evolve schemas safely with ALTER TABLE operations By following these best practices, you’ll lay the foundation for reliable, scalable databases that adapt to changing business needs. 1. Defining Tables with CREATE TABLE 1.1 Core Syntax The CREATE TABLE statement introduces a new table and its columns to the database. Always specify columns explicitly along with their data types and constraints: sql CREATE TABLE table_name ( column1_name data_type [constraints], column2_name data_type [constraints], …, columnN_name data_type [constraints] ); table_name : your chosen table identif...

  Designing a robust database schema is crucial for data integrity, performance, and long‐term maintainability. In this module, we’ll cover: Creating and altering tables Defining keys and leveraging indexes By the end, you’ll know how to structure your data model to support reliable applications and fast queries. Creating and Altering Tables A well‐designed table lays the foundation of your database. Start by defining clear columns, appropriate data types, and necessary constraints. 1. CREATE TABLE Syntax sql CREATE TABLE employees ( employee_id SERIAL PRIMARY KEY, first_name VARCHAR(50) NOT NULL, last_name VARCHAR(50) NOT NULL, hire_date DATE NOT NULL, email VARCHAR(100) UNIQUE, salary NUMERIC(10, 2) CHECK (salary > 0) ); Key takeaways: Use SERIAL or IDENTITY for auto-incrementing primary keys. Choose string lengths ( VARCHAR ) based on real data. Apply NOT NULL to mandatory columns. Enforce business rules with CHECK constraints. 2. A...

Final Project – Part 5: Final Review and Export Congratulations — you have reached the final phase of the Excel Basic Course Final Project. In this part, you will refine your dashboard, check for errors, ensure professional quality, and export your work in a clean, shareable format. A dashboard is only complete when it is: Accurate Clear Consistent Easy to read Ready for presentation This final review ensures your work meets professional standards used in business reporting, corporate training, and international certifications. 1. Review the Dataset Start by revisiting your original dataset to ensure everything is clean and consistent. Checklist: No blank rows or columns No inconsistent capitalization No duplicated records No formatting inconsistencies No errors in numeric or date fields Use the following tools if needed: 2.5 Basic Data Cleaning 4.5 Removing Duplicates 6.3 Find and Replace / Go To S...