Introduction to Fundamental Aspects of SQL
This module will cover some of the fundamental aspects of SQL.
This includes what SQL is, why we use it, and how it is different from programming. You will also set up your database and propagate it with the
PUBS data so that you can use it for the rest of this course.
SQL commonly expanded as Structured Query Language, is a computer language designed for the retrieval and management of data in relational database management systems, database schema creation and modification,
and database object access control management. SQL has been standardized by both ANSI and ISO.
The Structured Query Language (SQL) comprises one of the fundamental building blocks of modern database architecture.
SQL defines the methods used to create and manipulate relational databases on all major platforms.
This module will discuss the inner workings of SQL.
By the time you have completed this module, you will have the fundamental knowledge you need to go out there and start working with databases.
Thew Structured Query Language is a special programming language designed for managing data held in a relational database management system
Originally based upon relational algebra and tuple relational calculus, SQL consists of a data definition language and a
data manipulation language
The scope of SQL includes data insert, query, update and delete, schema creation and modification, and data access control.
Although SQL is often described as a declarative language (4GL), it also includes procedural elements
SQL was one of the first commercial languages for Edgar F. Codd's
, as described in his influential 1970 paper, "A Relational Model of Data for Large Shared Data Banks."
Despite not entirely adhering to the relational model as described by Codd, it became the most widely used database language.
SQL became a standard of the American National Standards Institute (ANSI) in 1986, and of the International Organization for Standardization (ISO) in 1987.
Since then, the standard has been enhanced several times with added features.
Information may be the most valuable commodity in the modern world. It can take many different forms: accounting and payroll information, information about customers and orders, scientific and statistical data, graphics, and multimedia, to mention just a few.
We are virtually swamped with data, and we cannot afford to lose it. As a society, we produce and consume ever increasing amounts of information, and database management systems were created to help us cope with informational deluge.
These days we simply have too much data to keep storing it in fi e cabinets or cardboard boxes, and the data might come in all shapes and sizes.
The need to store large collections of persistent data safely and examine it from different angles, by multiple users, and update it easily when necessary, is critical for every enterprise.
Besides storing the information, which is what electronic fi es are for, we need to be able to find it when needed and to filter out what is unnecessary and redundant.
With the informational deluge brought about by Internet findability, the data formats have exploded, and most data comes unstructured: pictures, sounds, text, and so on.
The approach that served us for decades, which was shredding data according to some predefined taxonomy, gave in to the greater flexibility of unstructured and semistructured data, and all this can still fit under the umbrella of a database.
The databases evolved to accommodate all this, and their language, which was designed to work with characters and numbers, evolved along with it.
The concept of gathering and organizing data in a database replaced with the concept of a data hub with your data at the core, surrounded with ever less related data at the rim.