Big Data and AI

  Welcome to Data Analyst BI! If you’ve ever felt overwhelmed by rows, columns, and cryptic error messages when trying to write your first SQL query, you’re in the right place. Today we’re launching a comprehensive SQL tutorial series crafted specifically for beginners. Whether you’re just starting your data career, pivoting from another field, or simply curious about how analysts slice and dice data, these lessons will guide you from day zero to confident query builder. In each installment, you’ll find clear explanations, annotated examples, and hands-on exercises. By the end of this series, you’ll be able to: Write efficient SQL queries to retrieve and transform data Combine multiple tables to uncover relationships Insert, update, and delete records safely Design robust database schemas with keys and indexes Optimize performance for large datasets Ready to master SQL in a structured, step-by-step way? Let’s explore the full roadmap ahead. Wh...

  Inserting Records · Updating Records · Deleting Records Modifying data—adding new rows, updating existing ones, and removing obsolete entries—is the flip side of querying. Without the ability to change data, databases become static archives. In this detailed guide, you’ll learn step by step how to insert, update, and delete records safely and efficiently in a relational database. Inserting Records Every database starts empty. The INSERT statement populates tables with new rows. You’ll discover how to add single records, bulk load data from other queries, and handle conflicts or defaults. 1. Single-Row Inserts Use INSERT INTO … VALUES to add one row at a time. Always specify the column list to avoid mismatches when the schema changes. sql INSERT INTO employees (first_name, last_name, email, hire_date, salary) VALUES ('Jane', 'Doe', 'jane.doe@example.com', '2025-08-15', 60000); Key points: Match the order of columns and values exactly. Omit columns wit...

  Part IV: Modifying Data – Chapter 9: Inserting Records Adding new data into your database is as critical as querying it. A solid INSERT strategy prevents downtime, avoids schema breakage, and ensures data accuracy from day one. In this chapter, we’ll cover: Basic INSERT INTO … VALUES syntax Bulk inserts using INSERT INTO … SELECT Best practices for batching large imports Verifying inserted data before committing By the end, you’ll have a reliable workflow for populating your tables safely and efficiently. 1. Basic INSERT INTO … VALUES Syntax The simplest way to add a row is with the INSERT … VALUES statement. Always specify columns explicitly to guard against schema changes. 1.1 Syntax Structure sql INSERT INTO table_name (col1, col2, ..., colN) VALUES (val1, val2, ..., valN); table_name : target table (col1, …, colN) : list of columns in the insertion order VALUES : literal values matching each column’s data type 1.2 Example: Single-Row Insert Imagine an employees table: sql C...

  Chapter 10: Updating and Deleting Maintaining data integrity while modifying existing records is a core responsibility for any database professional. In this chapter, we’ll explore how to: Craft safe UPDATE statements with precise WHERE filters Delete data responsibly using DELETE and TRUNCATE Control transactions with COMMIT, ROLLBACK, and SAVEPOINT Leverage backups and test environments to prevent data loss Mastering these techniques ensures your production workflows are reliable, reversible, and free from unexpected data corruption. 1. Why Safe Data Modification Matters Uncontrolled UPDATEs or DELETEs can irreversibly alter or remove critical business information. Key risks include: Accidentally updating all rows by omitting a WHERE clause Deleting entire tables instead of targeted records Leaving partial changes due to interrupted operations Violating referential integrity and breaking application logic By applying rigorous safeguards—filters, transactions, and testing—you pr...

  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...

Lesson 4.3 – Filtering Data Filtering allows you to display only the rows that match specific criteria while temporarily hiding the rest. It is one of the most useful tools in Excel for exploring, cleaning, and analyzing data without modifying or deleting anything. 1. What Is Filtering? Filtering helps you focus on the information you need by showing only the rows that meet your conditions. You can filter text, numbers, dates, and even colors. Examples: Show only “Electronics” products Display sales greater than 500 Show dates from the last 30 days Filter rows with a specific color 2. How to Apply a Filter Method 1 – Using the Ribbon: Select your dataset. Go to Home → Sort & Filter → Filter . Filter arrows will appear on each column header. Method 2 – Using a Table: If your data is formatted as an Excel Table, filters are automatically enabled. 3. Filtering Text Text filters allow you to show rows that match specif...