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Introduction to Data Analysis and Statistics Using SQL
Introduction to Data Analysis and Statistics Using SQL
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 2 Hours | Lec: 31 | 170 MB
Genre: eLearning | Language: English

Hands-on Practical Data Analysis Using SQL

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 .


Hands-on Practical Data Analysis Using SQL
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 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 payment-all 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
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Tags: introduction, analysis, statistics

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