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Part II: Retrieving Data with SQL

Retrieving data is the heart of SQL. In Part II of our beginner-friendly tutorial series, we’ll dive into the four essential techniques that let you extract, filter, summarize, and refine datasets: Basic SELECT Queries Advanced Filtering and Expressions Aggregation and Grouping Subqueries and Derived Tables Mastering these topics will empower you to answer real-world questions, from listing customer orders to calculating monthly sales trends. Basic SELECT Queries The SELECT statement is your gateway to any relational database. You’ll learn how to: Specify columns and use aliases ( SELECT first_name AS fname ) Retrieve all fields with SELECT * for quick previews Limit result sets ( LIMIT 10 , TOP 5 ) to speed up testing Sort data with ORDER BY (ascending/descending) Example: sql SELECT id, first_name, last_name FROM customers ORDER BY last_name ASC; This simple query fetches a clean, ordered list of customer names in seconds. Advanced Filtering and Expressions Once you can pull r...

Part VI: Limitations and Best Practices

Turning Fibonacci from a visual crutch into a robust decision framework Fibonacci retracement is seductive: clean lines, iconic ratios, and the satisfying sense that price “respects” geometry. But markets are not Euclidean—they are noisy, adaptive, and reflexive. If you use Fibonacci as a drawing tool, you’ll get drawing-level results. If you use it as a framework—with standardized swing logic, probabilistic validation, confluence rules, and risk-first execution—you can turn those lines into a disciplined edge. This chapter dives very deep into where Fibonacci fails, why it fails, and how to engineer best practices that hold up in real trading and systematic testing. 6.1 Common pitfalls Subjectivity: swing points vary by timeframe and analyst Fibonacci analysis begins with picking a swing high and swing low, but that’s already a minefield. Ambiguous impulses: In real markets, you’ll often see overlapping swings, nested corrections, and failed breakouts. Your “obvious” swing might be a...

Part I: Getting Started with SQL Chapter 2: Setting Up Your Environment

Chapter 2: Setting Up Your Environment Before you write your first query, it’s essential to install and configure a relational database on your workstation. A solid environment ensures you spend time learning SQL—not battling installation errors. In this chapter, we’ll: Compare four popular RDBMS options Walk through installation on Windows, macOS, and Linux Demonstrate how to connect via command-line and graphical tools Load a sample database so you can start querying immediately By the end, your machine will be a fully functional SQL playground. 1. Choosing an RDBMS: MySQL, PostgreSQL, SQLite, SQL Server Different relational database systems excel in different scenarios. Here’s a quick comparison to help you pick one: Feature MySQL PostgreSQL SQLite SQL Server Use case Web apps, LAMP stacks Analytics, GIS, advanced SQL Lightweight, embedded apps Enterprise .NET, Windows ecosystems Licensing GPL (Community) / Commercial (Enterprise) Open Source (PostgreSQL License) Public domain...

Part I: Getting Started with SQL Chapter 1: Introduction to Databases and SQL

Chapter 1: Introduction to Databases and SQL In today’s data-driven world, information powers decisions at every level—from personal finance trackers to enterprise analytics platforms. Databases serve as the backbone for storing, organizing, and retrieving this information efficiently. In this chapter, we’ll explore why data lives in tables, familiarize you with core terminology, trace the origins of relational databases, and explain how SQL emerged as the universal language for data manipulation. What Is Data and Why We Store It in Tables Data represents facts, figures, and measurements collected from real-world activities. Without structure, raw data is difficult to query, analyze, or validate. Storing data in tables offers several advantages: Logical organization: Tables group related information into rows (records) and columns (attributes), making it easy to locate and interpret individual pieces of data. Consistency: Structured tables enforce uniform data types and formats, ...

Part I: Getting Started with SQL

Welcome to Part I of our beginner-friendly SQL tutorial series on Data Analyst BI. In this first module, you’ll learn the fundamentals of relational databases and get your environment ready for hands-on SQL practice. Whether you aim to become a Data Analyst, BI Developer, or just want to query data like a pro, mastering these SQL basics will set you on the path to success. Introduction to Databases and SQL Structured Query Language (SQL) is the universal standard for interacting with relational databases. Before writing your first query, it’s essential to understand: What is a Database? A database stores information in tables made up of rows (records) and columns (fields). Common examples include customer lists, sales transactions, or inventory logs. Why Relational Databases? Relational databases enforce data integrity through primary keys, foreign keys, and constraints. This structure makes it easy to join related tables and maintain consistent, accurate data. The Role of SQL SQ...