Data Analytics - SQL Lesson 01 - Introduction.pptx

SQL

1. Structured Query Language (SQL) Lesson 1 - Introduction

2. Topics Covered What is Data? What are Databases? Need of Databases Types of Databases How Data is Stored in Relational Databases? What is SQL? Why SQL? What is Data Science? Why is SQL required for Data Science?

3. Database Topic 1

4. What is Data? Derived from Latin word “datum” meaning single fact, entity or point of matter Data is collection of facts, information, or knowledge Examples Twitter tweets Company’s financial report Newsletter Sales data, Employee data, etc.

5. What are Databases? A database is an organized collection of structured information, or data, typically stored electronically in a computer system [ Source - Wikipedia] Source – Pixabay.com

6. Features of a Database Data are raw facts that constitute building blocks of information.  Database is a collection of information and a means to manipulate data. It allows, Easy Fast access Facilitate the processing of data.  

7. Need of Databases Data is easier to store Data is easier to manage Need multiple views of data Improved sharing of data High security of data Enforce quality data Better integrated data

8. Types of Databases Data is Flat files Files stored in parent/child manner Data stored in tabular manner Data was created as objects Large data stored across networks

9. Types of databases Relational Databases Hierarchical Databases Graph based Databases Operational Databases Distributed Databases Data Warehouse

10. Database Management System (DBMS) As per technopedia, A database management system ( DBMS ) is a software package designed to define, manipulate, retrieve and manage data in a database.

11. Source – BBC Bitesize DBMS - Application

12. Relational Database Management System (RDBMS) Topic 2

13. Relational Database Management System (RDBMS) A  relational database  is a digital database based on the relational model of data, as proposed by E. F. Codd in 1970. A software system used to maintain relational databases is a relational database management system (RDBMS). A RDBMS consists of fields, tables and records. Structured Query Language (SQL) is used for querying and maintaining the database. Some popular RDBMS systems are MySQL, MS SQL Server, IBM DB2, Oracle, PostgreSQL, Microsoft Access, etc.

14. Popular Relational Databases

15. Basic Elements of RDBMS Tables – collection of rows and columns e.g. Customer table as shown Records or Tuple – represents each row of the table Fields or Column name or Attribute – are the columns of the table Keys – establishes relationship between tables e.g. Cust Number

16. SQL Topic 3

17. What is SQL? SQL stands for Structured Query language, pronounced as "S-Q-L" or as "See-Quel". Initially developed @ IBM by Donald Chamberlin and Raymond Boyce (early 1970s) ANSI standard in 1986 and ISO standard in 1987 SQL skills are in popular demand in the industry SQL is the standard language for Relational Databases. SQL is used to create, insert, search, update and delete database records. SQL can do other operations including optimizing and maintenance of databases. Relational databases like MySQL, Oracle, MS SQL Server, Sybase, etc. use SQL.

18. Why SQL? Popular as it is easy to understand It is a declarative language Read and written similar to English language Directly accesses the stored data, hence it is very fast

19. Introduction to Data Science Topic 4

20. What is Data Science? Book on Prediction of Cancer Patient Outcomes Based on Artificial Intelligence - By Suk Lee, Eunbin Ju, etc.

21. How SQL fits into Data Science? Since data is at the core of Data Science, there is a frequent need to store and access data Data could be very large -- of the order of millions and billions data points Hence SQL is needed SQL

22. Big Picture Source - www.sql-datatools.com

23. Key Takeaways Data is a everywhere, hence databases are used to store and manage data Databases can be relational or non-relational The basic elements of a RDBMS are tables, rows, columns, keys SQL is a structured query language and a vital tool for accessing and manipulating data in the entire Data Science life cycle

24. Queries?