In the year 1970’s when relational database came into picture, data schema to be worked upon were reasonably elemental and simple wherein the data items were to be arranged as a set of formally described tables with rows and columns. But with the need to store volumes and variety of data (unstructured) in recent years, non-relational database technologies            (document-oriented, graph based, column based, key-value and hybrid) have emerged to address the requirement that allow data to be grouped together more naturally and logically. One of the most popular ways of storing data is a document-oriented database, basically employed for storing, managing and retrieval of semi-structured data where each record and its associated data is considered of as a “document”. A document-oriented database is also termed as a document store or simple document, is one of the kind of NoSQL database. 

With the expansion of huge and complex real time data that is wandering across the internet today, the dimensions of data transmitted are escalating exponentially with each passing years. This makes working with standard database systems or on personal computers difficult because of its inability to handle outsized, unstructured and complicated data. Various institutes stores and uses massive amounts of data which are further utilized for generating reports to guarantee stability regarding the services they proposes. However, the challenge is how to analyze, capture, share, store, transfer, visualize, query, update and finally manipulate an impressive volume of data that has to be delivered through the internet to reach its destination intact maintaining its information privacy. Almost all the applications developed using any programming languages requires some external component to store and access data. The components for the same could be a local network, a cloud file or even a database. While sources like the network and cloud file systems store the unstructured data, the structured data is usually stored in a typical Relational Database Management System or RDBMS. The RDBMS operates with relational data model using schema for storing data into tables and is usually queried with SQL (Structured Query Language) for data operations. Usually it’s a time consuming process to define, structure, distribute and access data from RDBMS through SQL and hence, an alternative was developed for this called the NoSQL ("Non SQL", "Non relational" or "Not only SQL") database. This edited book chapter provides NoSQL databases hands on and attention has been paid to various types of NoSQL databases focusing on the details such as installation, creation, modification and various updation of one database belonging to each type.

Welcome to “SQL and Database Management Using Pop Culture,” a GitHub repository that leads a double life as an interactive Database and SQL textbook. Through this innovative approach, we blend the technical world of SQL and database management with the relatable and often thrilling realm of pop culture. This book is designed to make the complex concepts of databases not just understandable but genuinely enjoyable to learn.

Why This Book? Databases are the backbone of the modern data-driven world, yet their intricacies can often seem labyrinthine to learners. This book demystifies these complexities by drawing parallels with popular culture, weaving a narrative that is both informative and relatable. Whether you are a student stepping into the world of databases or a professional seeking to deepen your understanding, this book provides a fresh perspective that is both comprehensive and accessible. The book starts with basic queries in SQLite, and move on to introduce both PostgreSQL and MySQL in later chapters. The content is aligned with the content of the CompTia Data Sys+ and Oracle Database Foundations exams.

The Structure of the Book. Each chapter of this book is crafted like an episode of a TV series, where learning SQL and database management becomes an adventure rather than a routine academic endeavor. Here’s what awaits you in this journey:

Chapter 0: Get started with an interactive introduction to SQL and Python in Colab notebooks.
Chapters 1 to 12: From the deck of the Star Trek Enterprise to the magical corridors of Hogwarts, dive into every aspect of SQL and database management. Each chapter unfolds a new scenario, tying complex database concepts to familiar stories and characters from pop culture.
This repository houses twelve Jupyter notebooks, making the learning experience highly interactive and hands-on. You’ll not just read about SQL queries and database theories but also get to experiment and see the results in real-time.