List of notebooks/cheatsheets and more focused on SQL

CRUD is the acronym for CREATE, READ, UPDATE and DELETE. These terms describe the four essential operations for creating and managing persistent data elements, mainly in relational and NoSQL databases.

• ACID is an acronym for four interdependent properties: Atomicity, Consistency, Isolation, and Durability. Much of the architecture of any modern relational database is founded on these properties. Understanding the ACID properties of a transaction is a prerequisite for understanding many facets of SQL Server.
  • Atomic – Transaction acting on several pieces of information complete only if all pieces successfully save. Here, “all or nothing” applies to the transaction.
  • Consistent – The saved data cannot violate the integrity of the database.
  • Isolation – No other transactions take place and affect the transaction in question. This prevents “mid-air collisions.”
  • Durable – System failures or restarts do not affect committed transactions.

• Normalisation is the process to eliminate data redundancy and enhance data integrity in the table. Normalsation also helps to organize the data in the database. It is a multi-step process that sets the data into tabular form and removes the duplicated data from the relational tables.
• Normalisation organises the columns and tables of a database to ensure that database integrity constraints properly execute their dependencies. It is a systematic technique of decomposing tables to eliminate data redundancy (repetition) and undesirable characteristics like Insertion, Update, and Deletion anomalies.

Each notebook has two versions (all python scripts are unaffected by this):

• One where all the markdown comments are rendered in black and white. These are placed in the folder named GitHub_MD_rendering where MD stands for MarkDown.
• One where all the markdown comments are rendered in coloured.

• www.w3schools.com has some very nice tutorials where you can also try out your code in an interpreter running on their web browser.
• w3schools offere a live SQL server with some tables available. Probably the easiest, cheapest and quickiest way to start practicing SQL queries.
• leetcode also allows you to try out some problem directly on your browser.
• DataLemur
• SQLpad
• Mode
• Strat Scratch
• SQL Zoo
• Hacker Rank
• SQL-Practice
• Programiz
• Superintendent.app | You can write SQL to query and visualize gigabytes of CSV files on your local machine.

• JupySQL: Better SQL in Jupyter

• MySQL is an open-source relational database system.
• Oracle SQL is also a relational database system but it's not open-source.
• PostgreSQL is an open-source, object-relational database management system. It is fully SQL-compliant and was built to be feature-rich.
• Imapala SQL is a MPP (Massive Parallel Processing) SQL query engine for processing huge volumes of data that is stored in Hadoop cluster. It is an open source software which is written in C++ and Java. I
• Hive SQL allows users to read, write, and manage petabytes of data using SQL. Hive is built on top of Apache Hadoop, which is an open-source framework used to efficiently store and process large datasets.
• SQlite is a C-language library that implements a small, fast, self-contained, high-reliability, full-featured, SQL database engine. SQLite is the most used database engine in the world.
• T-SQL stands for transact-SQL. It is a set of programming extensions from Sybase and Microsoft that add several features to the Structured Query Language (SQL), including transaction control, exception and error handling, row processing and declared variables. While T-SQL is an extension to SQL, SQL is a programming language. T-SQL contains procedural programming and local variable, while SQL does not. T-SQL is proprietary, while SQL is an open format.

• In big data analytics, using a subquery is not efficient to process millions of rows of data. Using joins would be a better approach as most RDBMS's are optimized for joins.

• Often the jons are exaplained via Ven diagrams but this is highgly confusing. There are cases where this is not enough to explain the differences.
• One such a case is with CROSS JOIN and OUTER JOIN where both ven diagram looks like the same but internally in SQL they have a different meaning!

• The Not-so-Sexy SQL Concepts to Make You Stand Out
• https://www.kdnuggets.com/2021/10/data-science-sql-interview-questions.html
• https://e2eml.school/sql_resources.html
• https://realpython.com/pandas-groupby/
• https://github.com/imrankhan17/apprentices-training/tree/master/session3
• MySQL vs Oracle SQL
• PostgreSQL vs MySQL: Explore Their 12 Critical Differences
• Advanced SQL Puzzles
• The Querynomicon - An Introduction to SQL for Weary Data Scientists
• When do you prefer SQL or Python for Data Engineering?
• Bird's eyeys view of SQL