Introduction to Data Analysis and Statistics Using SQL

Course details

Descriptive statistics help us understand the overall structure of data, and SQL is the most widely used language for manipulating it. Together, they can help data analysts derive better insights and make far-reaching predictions. This course provides an overview of basic descriptive statistics and analytic SQL commands you need to know to summarise data sets, find averages, count, max and min value and calculate other analytic and statistical information relating to data contained in the database.

SQL Server is a relational database management system -RDBMS developed and owned by Microsoft.Thousands of companies all over the world use SQL Server for their data solution .
SQL -Structured Query Language is an internationally recognised language used to communicate and manipulate various database systems.

T-SQL - Transact SQL is Microsoft's implementation of SQL. There are a lot of similarities between them but also proprietary parts that are specific to SQL Server.
SQL can be used for Data Analysis to transform data already present in the database to valuable useful information that help companies and organisations make key business and management decisions.
This course is a beginners guide to performing data analysis and statistics using SQL to interrogate SQL Server to provide answers to data related questions. You will learn to write useful SQL queries that is applicable to the Real World production environment.
Everywhere data is being collected, every transaction, every web page visit, every paymentall these and much, much more are filling relational databases with raw data that can be analysed to provide useful information.

There is a demand for people who can use data to perform reporting and analysis thus helping businesses and organizations make important and critical decisions.

Topic covered include:

• Install SQL Server 2017
• Load sample database
• Introduction to Aggregate Functions
• AVG
• MIN
• MAX
• SUM
• COUNT
• GROUPING
• VAR
• VARP
• Introduction to Ranking Functions
• RANK
• NTILE
• DENSE_RANK
• ROW_NUMBER
• Introduction to Analytic Functions
• LEAD
• LAG
• LAST_VALUE
• FIRST_VALUE
• PERCENT_RANK
• CUM_DIST
• PERCENTILE_DISC
• PERCENTILE-CONT