Data & Business Analytics With SQL

You will work with real-world datasets and learn how to: Write basic SQL queries, Group and aggregate data to produce summary statistics, Join tables and apply filters and sub-queries, Write functions to explore and manipulate data, Communicate your insights to stakeholders No prior SQL knowledge required—start your journey to confidently pass the Data Analyst in SQL certification and more.

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Data Analytics with SQL Master Program

Who this course is for:

Aspiring Data Analysts or Business Intelligence Analysts looking to break into these fields by learning SQL.
Data Scientists trying to improve their data cleaning and transformation skills by learning SQL.

Non-technical business professionals such as business analysts and project managers trying to gain a better understanding of the technical domains they interact with.

What you will Learn:

Use SQL to apply complex criteria and transformations to database data.
Master SQL functions for sophisticated data manipulation.

Leverage an understanding of relational database design to link together data stored across multiple tables.
Use aggregate queries to produce summarized views and analysis.

Be comfortable putting SQL and SQL Server on your resume.
Gain experience with the kind of SQL coding problems you are likely to encounter in an interview.

Course Benefits & Key Features

Data Analysis with SQL’s benefits and key features.

Modules

30+ Modules.

Lessons

80+ Lessons

Practical

40+ Hands-On Labs

Life Projects

5+ Projects

Resume

CV Preparations

Job

Jobs Reference

Recording

Session Recording

Interviews

Mock Interviews

Support

On Job Supports

Membership

Membership Access

Networks

Networking

Certification

Certificate of Completion

INSTRUCTOR-LED LIVE ONLINE CLASSES

Our learn-by-building method enables you to build

practical or coding experience that sticks. 95% of our

learners say they have confidence and remember more

when they learn by building real world projects, which is

required to work in your real life.

Get step-by-step guidance to practice your skills without getting stuck
Validate your technical problem-solving skills in a real environment
Troubleshoot complex scenarios to practice what you learned
Develop production experience that translates into real-world

.

Why Data Analytics With SQL Master Program?

Learn In-demand Skills

Those with careers in data analysis learn relevant in-demand skills that span industries and add value to every digital-enabled organization.

Earn a Higher Salary

Experienced data analysts can earn up to $112,000 per year and transition into higher-paying jobs as Senior Data Analysts, Data Scientists, or Analytics Managers.

Positive Job Outlook

The data analytics market is predicted to hit $132.90 Billion USD by 2026. COVID-19 pandemic accelerated the adoption of data analytics solutions and services.

Shape the Future

Data analysts transform organizations by capitalizing on data to improve their business decisions and solve critical real-world problems.

Become a Leader

Being a central part of an organization’s decision-making processes, analytics experts often pick up strong leadership skills as well.

Data Analysis are Constantly Evolving

Data analysis moves quickly, and data analysts are constantly learning and advancing in their careers.

GreaterHeight Certificates holders are prepared to work at companies like these.

Some Alumni Testimonies

Investing in the course "Become a Data Analyst" with GreaterHeight Academy is great value for the money and I highly recommend. The trainer is very knowledgeable, very engaging, provided us with quality training sessions on all courses and was easily acessible for queries. We also had access to the course materials and also the timely availability of the recorded videos made it easy and aided the learning process..

QUEEN OBIWULU

Team Lead, Customer Success

The training was fantastic, the instructor is an awesome lecturer, relentless and not tired in his delivery. He obviously enjoys teaching, it comes natural to him. We got more than we expected. He extended my knowledge of Excel beyond what I knew, and the courses were brilliantly delivered. They reach out, follow up, ask questions, and in fact the support has been great. They are highly recommended and I would definitely subscribe to other training programs from them.

BISOLA OGUNRO

Fraud Analytics Risk Oversight Manager

It's one thing to look for just a Data Analysis training, and it's another to get the knowledge transferred through certified professional trainers. No matter your initial level of proficiency in any of the Data Analysis tools, GreaterHeight Academy would meet you there and take you up to a highly proficienct and confident level in a short time at a reasonable pace. I learnt a lot of Data Analysis tools and skills at GreaterHeight from patient and resourceful teachers.

TUNDE MEREDITH

Operation Director - Abbfem Technology

The Data Analysis training program was one of the best I have attended. The way GreaterHeight took off with Excel and concluded the four courses with Excel was a mind blowing - it was WOW!! I concluded that I'm on the right path with the right mentor to take me from a novice to professional. GreaterHeight is the best as far as impacting Data Analysis knowledge is concern. I would shout it at the rooftop to recommend GreaterHeight to any trainee that really wants to learn.

JOHN OSI PETER

Greaterheight

I wanted to take a moment to express my deepest gratitude for the opportunity to study data analytics at GreaterHeight Academy. I am truly impressed by the level of dedication and support that the sponsor and CEO have put into this program. GreaterHeight Academy is without a doubt the best tech institution out there, providing top-notch education and resources for its students. One of the advantages of studying at GreaterHeight Academy is the access to the best tools and technologies in the field.

AYODELE PAYNE

Sales/Data Analyst

It is an unforgettable experience that will surely stand the test of time learning to become a Data Analyst with GreaterHeights Academy. The Lecture delivery was so impactful and the Trainer is vast and well knowledgeable in using the applicable tools for the Sessions. Always ready to go extra mile with you. The supports you get during and after the lectures are top notch with materials and resources available to build your confidence on and off the job.

ADEBAYO OLADEJO

Customer Service Advisor (Special Operations)

Data Analytics With SQL Master Program

Introduction to SQL

Learn how Relational Databases are Organized

SQL is an essential language for building and maintaining relational databases, which opens the door to a range of careers in the data industry and beyond. You’ll start this course by covering data organization, tables, and best practices for database construction.

Write Your First SQL Queries

The second half of this course looks at creating SQL queries for selecting data that you need from your database. You’ll have the chance to practice your querying skills before moving on to customizing and saving your results.

Understand the Difference Between PostgreSQL and SQL Server

PostgreSQL and SQL Server are two of the most popular SQL flavors. You’ll finish off this course by looking at the differences, benefits, and applications of each. By the end of the course, you’ll have some hands-on experience in learning SQL and the grounding to start applying it to projects or continue your learning in a more specialized direction.

5 Modules | 5+ Hours | 4+ Skills

Course Modules

Before writing any SQL queries, it’s important to understand the underlying data. In this module, we’ll discover the role of SQL in creating and querying relational databases. Using a database for a local library, we will explore database and table organization, data types and storage, and best practices for database construction.

Introduction to Database Management System
What are the advantages of databases?
Data organization
Introduction to SQL
Tables in SQL
Views in SQL
Table vs Views
Picking a unique ID
Setting the table in style
Finding data types

Introduction
Entity Relationship Model
Relationships in SQL
Recap

Introduction
Downloading SQL Developer Edition
Installing SQL Developer Edition
Connecting to SQL Server
Downloading Sample SQL Database in SQL Management Studio (SSMS)
Configuring SQL Server, and SSMS
Recap

Database Manipulation in SQL
SQL Storage Engines
Creating and Managing Tables in SQL
Creating and Managing Tables in SQL CREATE, DESCRIBE, and SHOW Table
Creating and Managing Tables in SQL ALTER, TRUNCATE, and DROP Tables
Inserting and Querying Data in Tables
Filtering Data From Tables in SQL
Filtering Data From Tables in SQL WHERE and DISTINCT Clauses
Filtering Data From Tables in SQL AND and OR Operators
Filtering Data From Tables in SQL IN and NOT IN Operators
Filtering Data From Tables in SQL BETWEEN and LIKE Operators
Filtering Data From Tables in SQL TOP, IS NULL, and IS NOT NULL Operators
Sorting Table Data
Recap

Learn your first SQL keywords for selecting relevant data from database tables! After practicing querying skills in a database of books, you’ll customize query results using aliasing and save them as views so they can be shared. Finally, you’ll explore the differences between SQL flavors and databases such as SQL Server.

Introducing queries
SQL strengths
Developing SQL style
Querying the books table
Writing queries
Comments in SQL
Making queries DISTINCT
Aliasing
Viewing your query
SQL flavors
Comparing flavors
Limiting results

Intermediate SQL

SQL is widely recognized as the most popular language for turning raw data stored in a database into actionable insights. This course uses a films database to teach how to navigate and extract insights from the data using SQL.

Discover Filtering with SQL

You'll discover techniques for filtering and comparing data, enabling you to extract specific information to gain insights and answer questions about the data.

Get Acquainted with Aggregation

Next, you'll get a taste of aggregate functions, essential for summarizing data effectively and gaining valuable insights from large datasets. You'll also combine this with sorting and grouping data, adding another layer of meaning to your insights and analysis.

Write Clean Queries

Finally, you'll be shown some tips and best practices for presenting your data and queries neatly. Throughout the course, you'll have hands-on practice queries to solidify your understanding of the concepts. By the end of the course, you'll have everything you need to know to analyze data using your own SQL code today!

7 Modules | 6+ Hours | 5+ Skills

Course Modules

In this first module, you’ll learn how to query a films database and select the data needed to answer questions about the movies and actors. You'll also understand how SQL code is executed and formatted.

SELECT Statement
SELECT DISTINCT
Query execution
Order of execution
SQL style
SQL best practices
Formatting
Non-standard fields

Arithmetic Operators: +, -, *, /, %
Comparison Operators: =, >, <, >=, <=, <>, !=
Logical Operators: AND, OR, NOT
Special Operators: LIKE, IN, NOT, NOT EQUAL, IS NULL, UNION , UNION ALL ,
| Except, Between, ALL and ANY, INTERSECT Clause, EXISTS

Learn about how you can filter numerical and textual data with SQL. Filtering is an important use for this language. You’ll learn how to use new keywords and operators to help you narrow down your query to get results that meet your desired criteria and gain a better understanding of NULL values and how to handle them.

Filtering numbers
Filtering results
Using WHERE with numbers
Using WHERE with text
Multiple criteria
Using AND
Using OR
Using BETWEEN
Filtering text
LIKE and NOT LIKE
WHERE IN
Combining filtering and selecting
Understanding NULL values
Practice with NULLs

Here, we will teach you how to sort and group data. These skills will take your analyses to a new level by helping you uncover critical business insights and identify trends and performance. You'll get hands-on experience to determine which films performed the best and how movie durations and budgets changed over time.

Sorting results
Sorting text
The SQL ORDER BY
ORDER BY - ascending
ORDER BY - descending
Sorting single fields
Sorting multiple fields

Data Definition Language (DDL): CREATE, DROP, ALTER, TRUNCATE
Data Query Language (DQL): SELECT, WHERE
Data Manipulation Language (DML): INSERT, UPDATE, DELETE

NOT NULL Constraints
UNIQUE Constraints
Primary Key Constraints
Foreign Key Constraints
Composite Key
Unique Constraints
Alternate Key
CHECK Constraints
DEFAULT Constraints

SQL allows you to zoom in and out to better understand an entire dataset, its subsets, and its individual records. You'll learn to summarize data using aggregate functions and perform basic arithmetic calculations inside queries to gain insights into what makes a successful film.

COUNT, SUM, AVG, MIN, MAX, Num
Summarizing data
Aggregate functions and data types
Practice with aggregate functions
Summarizing subsets
Grouping data
GROUP BY single fields
GROUP BY multiple fields
Answering business questions
Filtering grouped data
Filter with HAVING
HAVING and sorting
Combining aggregate functions with WHERE
Using ROUND()
ROUND() with a negative parameter
Aliasing and arithmetic
Using arithmetic
Aliasing with functions
Rounding results

Joining Data In SQL

Joining data is an essential skill in data analysis, enabling you to draw information from separate tables together into a single, meaningful set of results. In this comprehensive course on joining data, you'll delve into the intricacies of table joins and relational set theory, learning how to optimize your queries for efficient data retrieval.

Understand Data Joining Fundamentals

You will learn how to work with multiple tables in SQL by navigating and extracting data from various tables within a SQL database using various join types, including inner joins, outer joins, and cross joins. With practice, you'll gain the knowledge of how to select the appropriate join method.

Explore Advanced Data Manipulation Techniques

Next up, you'll explore set theory principles such as unions, intersects, and except clauses, as well as discover the power of nested queries in SQL. Every step is accompanied by exercises and opportunities to apply the theory and grow your confidence in SQL.

5 Modules | 5+ Hours | 4+ Skills

Course Modules

Introduction to Alias
Introduction to JOINS
Right Cross and Self Join
Operators in SQL
Operators in SQL Updated
Intersect and Emulation
Minus and Emulation
Subquery in SQL
Subqueries with Statements and Operators
Subqueries with Commands
Derived Tables in SQL
EXISTS Operator
NOT EXISTS Operator
EXISTS vs IN Operators
Recap

In this closing Module, you’ll begin by investigating semi-joins and anti-joins. Next, you'll learn how to use nested queries. Last but not least, you’ll wrap up the course with some challenges!

Subquerying with semi joins and anti joins
Multiple WHERE clauses
Semi join
Diagnosing problems using anti join
Subqueries inside WHERE and SELECT
Subquery inside WHERE
WHERE do people live?
Subquery inside SELECT
Subqueries inside FROM
Subquery inside FROM
Subquery challenge
Final challenge
The finish line

In this module, you’ll be introduced to the concept of joining tables and will explore all the ways you can enrich your queries using joins—beginning with inner joins.

The ins and outs of INNER JOIN
Your first join
Joining with aliased tables
USING in action
Defining relationships
Relationships in our database
Inspecting a relationship
Multiple joins
Joining multiple tables
Checking multi-table joins

After familiarizing yourself with inner joins, you will come to grips with different kinds of outer joins. Next, you will learn about cross joins. Finally, you will learn about situations in which you might join a table with itself.

LEFT and RIGHT JOINs
Remembering what is LEFT
This is a LEFT JOIN, right?
Building on your LEFT JOIN
Is this RIGHT?
FULL JOINs
Comparing joins
Chaining FULL JOINs
Crossing into CROSS JOIN
Histories and languages
Choosing your join
Self joins
Comparing a country to itself
All joins on deck

In this module, you will learn about using set theory operations in SQL, with an introduction to UNION, UNION ALL, INTERSECT, and EXCEPT clauses. You’ll explore the predominant ways in which set theory operations differ from join operations.

Set theory for SQL Joins
UNION vs. UNION ALL
Comparing global economies
Comparing two set operations
At the INTERSECT
INTERSECT
Review UNION and INTERSECT
EXCEPT
You've got it, EXCEPT...
Calling all set operators

Data Manipulation In SQL

Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in SQL.

So you've learned how to aggregate and join data from tables in your database—now what? How do you manipulate, transform, and make the most sense of your data? This intermediate-level course will teach you several key functions necessary to wrangle, filter, and categorize information in a relational database, expand your SQL toolkit, and answer complex questions. You will learn the robust use of CASE statements, subqueries, and window functions—all while discovering some interesting facts about soccer using the European Soccer Database.

4 Modules | 5+ Hours | 4 Skills

Course Modules

In this module, you will learn how to use the CASE WHEN statement to create categorical variables, aggregate data into a single column with multiple filtering conditions, and calculate counts and percentages.

Basic CASE statements
CASE statements comparing column values part 1
CASE statements comparing two column values part 2
Using CASE statement when things get more complex
Using CASE statement in case of rivalry
Filtering your CASE statement
CASE WHEN with aggregate functions
COUNT using CASE WHEN
COUNT and CASE WHEN with multiple conditions
Calculating percent with CASE and AVG

In this module, you will learn about subqueries in the SELECT, FROM, and WHERE clauses. You will gain an understanding of when subqueries are necessary to construct your dataset and where to best include them in your queries.

WHERE are the Subqueries?
Filtering using scalar subqueries
Filtering using a subquery with a list
Filtering with more complex subquery conditions
Subqueries in FROM
Joining Subqueries in FROM
Building on Subqueries in FROM
Subqueries in SELECT
Add a subquery to the SELECT clause
Subqueries in Select for Calculations
Subqueries everywhere! And best practices!
ALL the subqueries EVERYWHERE
Add a subquery in FROM
Add a subquery in SELECT

In this module, you will learn how to use nested and correlated subqueries to extract more complex data from a relational database. You will also learn about common table expressions and how to best construct queries using multiple common table expressions.

Correlated subqueries
Basic Correlated Subqueries
Correlated subquery with multiple conditions
Nested subqueries
Nested simple subqueries
Nest a subquery in FROM
Common Table Expressions
Clean up with CTEs
Organizing with CTEs
CTEs with nested subqueries
Deciding on techniques to use
Get team names with a subquery
Get team names with correlated subqueries
Get team names with CTEs

You will learn about window functions and how to pass aggregate functions along a dataset. You will also learn how to calculate running totals and partitioned averages.

Understanding OVER clause
The match is OVER
What's OVER here?
Flip OVER your results
OVER with a PARTITION
PARTITION BY a column
PARTITION BY multiple columns
Sliding windows
Slide to the left
Slide to the right
Bringing it all together
Setting up the home team CTE
Setting up the away team CTE
Putting the CTEs together
Add a window function

SQL Summary Stats & Window Functions

Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!

Have you ever wondered how data professionals use SQL to solve real-world business problems, like generating rankings, calculating moving averages and running totals, deduplicating data, or performing time intelligence? If you already know how to select, filter, order, join and group data with SQL, this course is your next step. By the end, you will be writing queries like a pro! You will learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon! Using flights data, you will discover how simple it is to use window functions, and how flexible and efficient they are.

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4 Modules | 5+ Hours | 4 Skills

Course Modules

In this module, you'll learn what window functions are, and the two basic window function subclauses, ORDER BY and PARTITION BY.

Introduction
Window functions vs GROUP BY
Numbering rows
Numbering Olympic games in ascending order
ORDER BY
Numbering Olympic games in descending order
Numbering Olympic athletes by medals earned
Reigning weightlifting champions
PARTITION BY
Reigning champions by gender
Reigning champions by gender and event
Row numbers with partitioning

In this module, you'll learn three practical applications of window functions: fetching values from different parts of the table, ranking rows according to their values, and binning rows into different tables.

Fetching
Future gold medalists
First athlete by name
Last country by name
Ranking
Ranking athletes by medals earned
Ranking athletes from multiple countries
DENSE_RANK's output
Paging
Paging events
Top, middle, and bottom thirds

In this module, you'll learn how to use aggregate functions you're familiar with, like `AVG()` and `SUM()`, as window functions, as well as how to define frames to change a window function's output.

Aggregate window functions
Running totals of athlete medals
Maximum country medals by year
Minimum country medals by year
Frames
Number of rows in a frame
Moving maximum of Scandinavian athletes' medals
Moving maximum of Chinese athletes' medals
Moving averages and totals
Moving average's frame
Moving average of Russian medals
Moving total of countries' medals

In this last module, you'll learn some techniques and functions that are useful when used together with window functions.

Pivoting
A basic pivot
Pivoting with ranking
ROLLUP and CUBE
Country-level subtotals
All group-level subtotals
A survey of useful functions
Cleaning up results
Summarizing results

Functions for Manipulating Data in SQL

Learn the most important SQL functions for manipulating, processing, and transforming data.

This course will provide you an understanding of how to use built-in SQL functions in your SQL queries to manipulate different types of data including strings, character, numeric and date/time. We'll travel back to a time where Blockbuster video stores were on every corner and if you wanted to watch a movie, you actually had to leave your house to rent a DVD! You'll also get an introduction into the robust full-text search capabilities which provides a powerful tool for indexing and matching keywords in a SQL document. And finally, you'll learn how to extend these features by using PostgreSQL extensions.

4 Modules | 5+ Hours | 4 Skills

Course Modules

Learn about the properties and characteristics of common data types including strings, numeric and arrays and how to retrieve information about your database.

String Data types - Char, Varchar, Binary, Text, nvarchar, nchar, image, etc.
Numeric Data Types - bit, tinyint, SmallInt, Int, Integer, BigInt, decimal, numeric, float, real, etc.
Date & Time - Date, DateTime, Year,
Getting information about your database
Determining data types
Date and time data types
Properties of date and time data types
Interval data types

Explore how to manipulate and query date and time objects including how to use the current timestamp in your queries, extract subfields from existing date and time fields and what to expect when you perform date and time arithmetic.

Overview of basic arithmetic operators
Adding and subtracting date and time values
INTERVAL arithmetic
Calculating the expected return date
Functions for retrieving current date/time
Current timestamp functions
Working with the current date and time
Manipulating the current date and time
Extracting and transforming date/ time data
Using EXTRACT
Using DATE_TRUNC

Learn how to manipulate string and text data by transforming case, parsing and truncating text and extracting substrings from larger strings.

Reformatting string and character data - FORMAT()
Concatenating strings - CONCAT()
Changing the case of string data - LOWER()
Replacing string data - SUBSTR()
Parsing string and character data
Determining the length of strings - LEN()
Truncating strings - LTRIM(), RTRIM(), & TRIM()
Extracting substrings from text data - MID(), LEFT() & RIGHT()
Combining functions for string manipulation - - MID(), LEFT() & RIGHT()
Truncating and padding string data

An introduction into some more advanced capabilities of SQL like full-text search and extensions.

Introduction to full-text search
A review of the LIKE operator
What is a tsvector?
Basic full-text search
Extending PostgreSQL
User-defined data types
Getting info about user-defined data types
User-defined functions in Sakila
Intro to PostgreSQL extensions
Enabling extensions
Measuring similarity between two strings
Levenshtein distance examples
Putting it all together
Wrap Up

Introduction to Statistics

Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

Statistics are all around us, from marketing to sales to healthcare. The ability to collect, analyze, and draw conclusions from data is not only extremely valuable, but it is also becoming commonplace to expect roles that are not traditionally analytical to understand the fundamental concepts of statistics. This course will equip you with the necessary skills to feel confident in working with analyzing data to draw insights. You'll be introduced to common methods used for summarizing and describing data, learn how probability can be applied to commercial scenarios, and discover how experiments are conducted to understand relationships and patterns. You'll work with real-world datasets including crime data in London, England, and sales data from an online retail company

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4 Modules | 5+ Hours | 4 Skills

Course Modules

Summary statistics gives you the tools you need to describe your data. In this chapter, you'll explore summary statistics including mean, median, and standard deviation, and learn how to accurately interpret them. You'll also develop your critical thinking skills, allowing you to choose the best summary statistics for your data.

What is statistics?
Using statistics in the real-world
Identifying data types
Descriptive vs. Inferential statistics
Measures of center
Typical number of robberies per London Borough
Choosing a measure
London Boroughs with most frequent crimes
Measures of spread
Defining measures of spread
Box plots for measuring spread
Which crime has the larger standard deviation

Probability underpins a large part of statistics, where it is used to calculate the chance of events occurring. You'll work with real-world sales data and learn how data with different values can be interpreted as a probability distribution. You'll find out about discrete and continuous probability distributions, including the discovery of the normal distribution and how it occurs frequently in natural events!

What are the chances?
What is more likely?
Chances of the next sale being more than the mean
Conditional probability
Dependent vs. Independent events
Orders of more than 10 basket products
Discrete distributions
Identifying distributions
Sample mean vs. Theoretical mean
Continuous distributions
Discrete vs. Continuous distributions
Finding the normal distribution
Calculating probability with a uniform distribution

It's time to explore more probability distributions. You'll learn about the binomial distribution for visualizing the probability of binary outcomes, and one of the most important distributions in statistics, the normal distribution. You'll see how distributions can be described by their shape, along with discovering the Poisson distribution and its role in calculating the probabilities of events occuring over time. You'll also gain an understanding of the central limit theorem!

The binomial distribution
Recognizing a binomial distribution
How probability affects the binomial distribution
Identifying n and p
The normal distribution
Recognizing the normal distribution
What makes the normal distribution special?
Identifying skewness
Describing distributions using kurtosis
The central limit theorem
Visualizing sampling distributions
The CLT vs. The law of large numbers
When to use the central limit theorem
The Poisson distribution
Identifying Poisson processes
Recognizing lambda in the Poisson distribution

In the final module, you'll be introduced to hypothesis testing and how it can be used to accurately draw conclusions about a population. You'll discover correlation and how it can be used to quantify a linear relationship between two variables. You'll find out about experimental design techniques such as randomization and blinding. You'll also learn about concepts used to minimize the risk of drawing the wrong conclusion about the results of hypothesis tests!

Hypothesis testing
Sunshine and sleep
The hypothesis testing workflow
Independent and dependent variables
Experiments
Recognizing controlled trials
Why use randomization?
Correlation
Identifying correlation between variables
What can correlation tell you?
Confounding variables
Interpreting hypothesis test results
Significance levels vs. p-values
Type I and type II errors

Exploratory Data Analysis in SQL

Learn how to explore what's available in a database: the tables, relationships between them, and data stored in them.

You have access to a database. Now what do you do? Building on your existing skills joining tables, using basic functions, grouping data, and using subqueries, the next step in your SQL journey is learning how to explore a database and the data in it. Using data from Stack Overflow, Fortune 500 companies, and 311 help requests from Evanston, IL, you'll get familiar with numeric, character, and date/time data types. You'll use functions to aggregate, summarize, and analyze data without leaving the database. Errors and inconsistencies in the data won't stop you! You'll learn common problems to look for and strategies to clean up messy data. By the end of this course, you'll be ready to start exploring your own SQL databases and analyzing the data in them.

4 Modules | 5+ Hours | 4 Skills

Course Modules

Start exploring a database by identifying the tables and the foreign keys that link them. Look for missing values, count the number of observations, and join tables to understand how they're related. Learn about coalescing and casting data along the way.

What's in the database?
Explore table sizes
Count missing values
Join tables
The keys to the database
Foreign keys
Read an entity relationship diagram
Coalesce
Column types and constraints
Effects of casting
Summarize the distribution of numeric values

You'll build on functions like min and max to summarize numeric data in new ways. Add average, variance, correlation, and percentile functions to your toolkit, and learn how to truncate and round numeric values too. Build complex queries and save your results by creating temporary tables.

Numeric data types and summary functions
Division
Explore with division
Summarize numeric columns
Summarize group statistics
Exploring distributions
Truncate
Generate series
More summary functions
Correlation
Mean and Median
Creating temporary tables
Create a temp table
Create a temp table to simplify a query
Insert into a temp table

Text, or character, data can get messy, but you'll learn how to deal with inconsistencies in case, spacing, and delimiters. Learn how to use a temporary table to recode messy categorical data to standardized values you can count and aggregate. Extract new variables from unstructured text as you explore help requests submitted to the city of Evanston, IL.

Character data types and common issues
Count the categories
Spotting character data problems
Cases and spaces
Trimming
Exploring unstructured text
Splitting and concatenating text
Concatenate strings
Split strings on a delimiter
Shorten long strings
Strategies for multiple transformations
Create an "other" category
Group and recode values
Create a table with indicator variables

What time is it? In this chapter, you'll learn how to find out. You'll aggregate date/time data by hour, day, month, or year and practice both constructing time series and finding gaps in them.

Date/time types and formats
ISO 8601
Date comparisons
Date arithmetic
Completion time by category
Date/time components and aggregation
Date parts
Variation by day of week
Date truncation
Aggregating with date/time series
Find missing dates
Custom aggregation periods
Monthly average with missing dates
Time between events
Longest gap
Rats!

Data-Driven Decision Making in SQL

Learn how to analyze a SQL table and report insights to management.

In this course, you will learn how to use SQL to support decision making. It is based on a case study about an online movie rental company with a database about customer information, movie ratings, background information on actors and more. You will learn to apply SQL queries to study for example customer preferences, customer engagement, and sales development. This course also covers SQL extensions for online analytical processing (OLAP), which makes it easier to obtain key insights from multidimensional aggregated data.

4 Modules | 5+ Hours | 4 Skills

Course Modules

The first module is an introduction to the use case of an online movie rental company, called Movie. Now and focuses on using simple SQL queries to extract and aggregated data from its database.

Introduction to data driven decision making
Exploring the database
Exploring the table renting
Filtering and ordering
Working with dates
Selecting movies
Select from renting
Aggregations - summarizing data
Summarizing customer information
Ratings of movie 25
Examining annual rentals

More complex queries with GROUP BY, LEFT JOIN and sub-queries are used to gain insight into customer preferences.

Grouping movies
First account for each country.
Average movie ratings
Average rating per customer
Joining movie ratings with customer data
Join renting and customers
Aggregating revenue, rentals and active customers
Movies and actors
Money spent per customer with sub-queries
Income from movies
Age of actors from the USA
Identify favorite actors of customer groups
Identify favorite movies for a group of customers
Identify favorite actors for Spain
KPIs per country

The concept of nested queries and correlated nested queries is introduced and the functions EXISTS and UNION are used to categorize customers, movies, actors, and more.

Nested query
Often rented movies
Frequent customers
Movies with rating above average
Correlated nested queries
Analyzing customer behavior
Customers who gave low ratings
Movies and ratings with correlated queries
Queries with EXISTS
Customers with at least one rating
Actors in comedies
Queries with UNION and INTERSECT
Young actors not coming from the USA
Dramas with high ratings

The OLAP extensions in SQL are introduced and applied to aggregated data on multiple levels. These extensions are the CUBE, ROLLUP and GROUPING SETS operators.

OLAP: CUBE operator
Groups of customers
Categories of movies
Analyzing average ratings
ROLLUP
Number of customers
Analyzing preferences of genres across countries
GROUPING SETS
Queries with GROUPING SETS
Exploring nationality and gender of actors
Exploring rating by country and gender
Bringing it all together
Customer preference for genres
Customer preference for actors

Understanding Data Visualization

An introduction to data visualization with no coding involved.

Visualizing data using charts, graphs, and maps is one of the most impactful ways to communicate complex data. In this course, you’ll learn how to choose the best visualization for your dataset, and how to interpret common plot types like histograms, scatter plots, line plots and bar plots. You'll also learn about best practices for using colors and shapes in your plots, and how to avoid common pitfalls. Through hands-on exercises, you'll visually explore over 20 datasets including global life expectancies, Los Angeles home prices, ESPN's 100 most famous athletes, and the greatest hip-hop songs of all time.

4 Modules | 5+ Hours | 4 Skills

Course Modules

In this module you’ll learn the value of visualizations, using real-world data on British monarchs, Australian salaries, Panamanian animals, and US cigarette consumption, to graphically represent the spread of a variable using histograms and box plots.

A plot tells a thousand words
Motivating visualization
Continuous vs. categorical variables
Histograms
Interpreting histograms
Adjusting bin width
Box plots
Interpreting box plots
Ordering box plots

You’ll learn how to interpret data plots and understand core data visualization concepts such as correlation, linear relationships, and log scales. Through interactive exercises, you’ll also learn how to explore the relationship between two continuous variables using scatter plots and line plots. You'll explore data on life expectancies, technology adoption, COVID-19 coronavirus cases, and Swiss juvenile offenders. Next you’ll be introduced to two other popular visualizations—bar plots and dot plots—often used to examine the relationship between categorical variables and continuous variables. Here, you'll explore famous athletes, health survey data, and the price of a Big Mac around the world.

Scatter plots
Interpreting scatter plots
Trends with scatter plots
Line plots
Interpreting line plots
Logarithmic scales for line plots
Line plots without dates on the x-axis
Bar plots
Interpreting bar plots
Interpreting stacked bar plots
Dot plots
Interpreting dot plots
Sorting dot plots

It’s time to make your insights even more impactful. Discover how you can add color and shape to make your data visualizations clearer and easier to understand, especially when you find yourself working with more than two variables at the same time. You'll explore Los Angeles home prices, technology stock prices, math anxiety, the greatest hiphop songs, scotch whisky preferences, and fatty acids in olive oil.

Higher dimensions
Another dimension for scatter plots
Another dimension for line plots
Using color
Eye-catching colors
Qualitative, sequential, diverging
Highlighting data
Plotting many variables at once
Interpreting pair plots
Interpreting correlation heatmaps
Interpreting parallel coordinates plots

In this final module, you’ll learn how to identify and avoid the most common plot problems. For example, how can you avoid creating misleading or hard to interpret plots, and will your audience understand what it is you’re trying to tell them? All will be revealed! You'll explore wind directions, asthma incidence, and seats in the German Federal Council.

Polar coordinates
Pie plots
Rose plots
Axes of evil
Bar plot axes
Dual axes
Sensory overload
Chartjunk
Multiple plots

Data Communication Concepts

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.

Learn the Basics of Data Communication

You’ve analyzed your data, run your model, and made your predictions. Now, it's time to bring your data to life! Presenting findings to stakeholders so they can make data-driven decisions is an essential skill for all data scientists. In this course, you’ll learn how to use storytelling to connect with your audience and help them understand the content of your presentation—so they can make the right decisions.

Explore Formats of Data Communication

Through hands-on exercises, you’ll learn the advantages and disadvantages of oral and written formats. You’ll also improve how you translate technical results into compelling stories, using the correct data, visualizations, and in-person presentation techniques. Start learning and improve your data storytelling today.

4 Modules | 5+ Hours | 4 Skills

Course Modules

Let's start with the importance of data storytelling and the elements you need to tell stories with data. You'll learn best practices to influence how decisions are made before learning how to translate technical results into stories for non-technical stakeholders.

Fundamentals of storytelling
The story begins
Building a story
Translating technical results
A non-tech story
Be aware
Impacting the decision-making process
Is it a true story?
Structured to impact
A story to compare

Deepen your storytelling knowledge. Learn how to avoid common mistakes when telling stories with data by tailoring your presentations to your audience. Then learn best practices for including visualizations and choosing between oral or written formats to make sure your presentations pack a punch!

Selecting the right data
The truth about salaries
Earning interests
Showing relevant statistics
Salary variation
On a payroll
It's not significant
Visualizations for different audiences
Salary development
Salary on demand
Choosing the appropriate format
A communication problem
Should we meet?
When in doubt

Now that you understand how to prepare for communicating findings, it’s time to learn how to structure your reports. You'll also learn the importance of reproducibility (work smarter, not harder) and how to get to the point when describing your findings. You’ll then get to apply all you’ve learned to a real-world use case as you create a compelling report on credit risk.

Types of reports
Something to report
In summary
Reproducibility and references
Replicate me
Same results
Write precise and clear reports
Half-empty glass
Strong words
Case study: report on credit risk
Credit me
Report my credit

You'll finish by learning simple techniques to structure a presentation, communicate insights, and inspire your audience to take action. Lastly, you'll learn how to improve your communication style and prepare to handle questions from your audience.

Planning an oral presentation
Is this the plan?
An effective plan!
Building presentation slides
A color building
Too much text
The right building
Delivering the presentation
Put it into practice
Best practice
Avoiding common errors
The true mistake
Do's and don'ts
Congratulations!

DATA ANALYTICS WITH SQL COST

United States

$549.99

United Kingdom

£499.99

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FAQs

Data Analytics With SQL Master Program

Yes, this career track, Database Design in SQL, is suitable for beginners. You do not need any prior SQL knowledge to start developing your SQL skills.

This track covers key concepts for building effective databases, and will be beneficial to individuals seeking jobs in a variety of roles such as Database Administrator, Data Analyst, Business Intelligence Analyst, Data Scientist, or SQL Developer.

Nowadays, information is gathered from a variety of root, and the information is of great value to organizations. However, with an increasing amount of data comes the need for a database that can entrepot information for retrieval and analysis by the trained specialist. Thus, proper data analysis is in high demand in our digital world.
A relational database, which logically group information into chunks, are basically used to store and organize large amounts of data. Of course, if you’re looking to retrieve any kind of information from a database, you need to speak its oral communication! The most widely used speech communication for interacting with the database is SQL (Structured Query Language), the amber standard of relational databases.
SQL queries, which are essentially requests or instructions that you send to a database, allow you to retrieve information and update, insert, or delete data. SQL is mainly associated with the IT sector and is an everyday instrument for database administrators. Developers use SQL to write an application that requires database connector, and systems architects use it to design database models. All of this mean value that encyclopedism SQL is a great choice for anyone who would like to pursue a career in IT.

The Business Intelligence market is growing significantly across the world and such strong growth pattern followed by market demand is a great opportunity for the following IT Professionals.

Business Analysts
Data Analysts
Project Managers
Data Scientists
Statisticians and Analysts
Business Intelligence Managers

SQL Certification Training Cost in USA, UK and NIGERIA is £300.

All online training classes are recorded. You will get the recorded sessions so that you can watch the online classes when you want. Also, you can join other class to do your missing classes.

A skill track is a collection of courses that help users acquire a specialized set of skills and knowledge within a certain area/domain. A career track focuses on a particular job/career where users can learn how to become a successful practitioner in that respective field.

GreaterHeight is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry ready.
You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc. After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.

There are no pre-requisites for this course, however, some fundamentals knowledge about DBMS will be beneficial.

All our mentors are highly qualified and experience professionals. All have at least 18-25 yrs. of development experience in various technologies and are trained by GreaterHeight Academy to deliver interactive training to the participants.

Yes, we do. As the technology upgrades, we do update our content and provide your training on latest version of that technology.

Exam Pattern for Tableau Desktop Certified Associate Exam

Time Limit: 2 hours; please plan for extra time for online exam setup.
Question Format: Multiple choice, true/false, multiple responses, hands-on
Number of Questions: 36
Scoring: Automatically scored; point value varies per question type with hands-on worth more
Passing score: 75%
Language(s) Offered: English, Simplified Chinese, Japanese, German, Brazilian Portuguese, French, International Spanish.
Delivery Platform: Windows Virtual Machine containing Tableau Desktop Source:
https://www.tableau.com/learn/certification/desktop-certified-associate

Yes, we would be providing you with the certificate of completion of the program once you have successfully submitted all the assessment and it has been verified by our subject matter experts.

Yes, we do. We will discuss all possible technical interview questions and answers during the training program so that you can prepare yourself for interview.

No. Any abuse of copyright is taken seriously. Thanks for your understanding on this one.

Yes. But you can also raise a ticket with the dedicated support team at any time. If your query does not get resolved through email, we can also arrange one-on-one sessions with our support team. However, our support is provided for a period of Twelve Weeks from the start date of your course.

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Data & Business Analytics With SQL

Data Analytics with SQL Master Program

Course Benefits & Key Features

Data Analysis with SQL’s benefits and key features.

Modules

Lessons

Practical

Life Projects

Resume

Job

Recording

Interviews

Support

Membership

Networks

Certification

INSTRUCTOR-LED LIVE ONLINE CLASSES

Why Data Analytics With SQL Master Program?

Learn In-demand Skills

Earn a Higher Salary

Positive Job Outlook

Shape the Future

Become a Leader

Data Analysis are Constantly Evolving

GreaterHeight Certificates holders are prepared to work at companies like these.

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Data Analytics With SQL Master Program

Module 1: Relational Databases

Module 2: Database Normalization and Entity Relationship (ER) Model

Module 3: Tools - Installation and Setup

Module 4: Working with Database and Tables in SSMS

Modules 5: Querying in TSQL

Module 1: Selecting Data

Module 2: Operators in SQL

Module 3: Filtering Records

Module 4: Sorting Records

Module 5: DDL, DQL, DML

Module 6: Constraints

Module 7: Grouping Data with Aggregate Functions for Data Analysis

Module 1: Subqueries, Operators, and Derived Tables in SQL

Module 2: Subqueries

Module 3: Introducing Inner Joins

Module 4: Outer Joins, Cross Joins and Self Joins

Module 5: Set Theory for SQL Joins

Module 1: Understanding the CASE statement

Module 2: Short and Simple Subqueries

Module 3: Correlated Queries, Nested Queries, and Common Table Expressions

Module 4: Window Functions

Module 1: Introduction to window functions

Module 2: Fetching, ranking, and paging

Module 3: Aggregate window functions and frames

Module 4: Beyond window functions

Module 1: Overview of Common Data Types

Module 2: Working with DATE/TIME Functions and Operators

Module 3: Parsing and Manipulating Text

Module 4: Full-text Search and SQL Extensions

Module 1: Summary Statistics

Module 2: Probability and distributions

Module 3: More Distributions and the Central Limit Theorem

Module 4: Correlation and Hypothesis Testing

Module 1: What's in the Database?

Module 2: Summarizing and Aggregating Numeric Data

Module 3: Exploring Categorical Data and Unstructured Text

Module 4: Working with Dates and Timestamps

Module 1: Introduction to business intelligence for a online movie rental database

Module 2: Decision Making with simple SQL queries

Module 3: Data Driven Decision Making with advanced SQL queries

Module 4: Data Driven Decision Making with OLAP SQL queries

Module 1: Visualizing distributions

Module 2: Visualizing two variables

Module 3: The color and the shape

Module 4: 99 problems but a plot ain't one of them

Module 1: Storytelling with Data

Module 2: Preparing to Communicate the Data