The Data Analytics Specialist Course

About Course

Hi! Welcome to The Business Intelligence Analyst Course, the only course you need to become a BI Analyst.

I am proud to present this one-of-a-kind opportunity. There are several online courses teaching some of the skills related to the BI Analyst profession. The truth of the matter is that none of them completely prepare you.

My program is different from the rest of the materials available online.

It is truly comprehensive. The course comprises several modules:

Introduction to Data and Data Science
Statistics and Excel
Database Theory
SQL
Tableau
SQL + Tableau

These are the precise technical skills recruiters are looking for when hiring BI Analysts. Today, you have the chance to gain an invaluable advantage over other candidates. This course will be the secret to your success. Your success is my success, so let’s make it happen!

Here are some more details of what you get with The Business Intelligence Analyst Course:

Introduction to Data and Data Science – Make sense of terms like business intelligence, traditional and big data, traditional statistical methods, machine learning, predictive analytics, supervised learning, unsupervised learning, reinforcement learning, and many more.
Statistics and Excel – Understand statistical testing and build a solid foundation. Modern software packages and programming languages are automating most of these activities, but this part of the course gives you something more valuable – critical thinking abilities.
Database Theory – Before you start using SQL, it is highly beneficial to learn about the underlying database theory and acquire an understanding of why databases are created and how they can help us manage data.
SQL – When you can work with SQL, it means you don’t have to rely on others sending you data and executing queries for you. You can do that on your own. This allows you to be independent and dig deeper into the data to obtain the answers to questions that might improve the way your company does its business.
Tableau – One of the most powerful and intuitive data visualization tools available. Almost all large companies use such tools to enhance their BI capabilities. Tableau is the #1 best-in-class solution that helps you create powerful charts and dashboards.
SQL + Tableau – Learning a programming language is meaningless without putting it to use. That’s why I integrate SQL and Tableau and perform several real-life Business Intelligence tasks.

Sounds amazing, right?

I will be there for you and provide support whenever necessary.

I love teaching, and I am really excited about this journey. It will get your foot in the door of an exciting and rising profession. Don’t hesitate to subscribe today. The only regret you will have is that you didn’t find this course sooner!

Become an expert in Statistics, SQL, Tableau, and problem solving
Boost your resume with in-demand skills
Gather, organize, analyze and visualize data
Use data for improved business decision-making
Present information in the form of metrics, KPIs, reports, and dashboards
Perform quantitative and qualitative business analysis
Analyze current and historical data
Discover how to find trends, market conditions, and research competitor positioning
Understand the fundamentals of database theory
Use SQL to create, design, and manipulate SQL databases
Extract data from a database writing your own queries
Create powerful professional visualizations in Tableau
Combine SQL and Tableau to visualize data from the source
Solve real-world business analysis tasks in SQL and Tableau

Course Content

Part 1: Introduction

What Does the Course Cover
Download All Resources

Intro to Data and Data Science – The Different Data Science Fields

Intro to Data and Data Science – The Relationship between Different Fields

Intro to Data and Data Science – What is the Purpose of each Data Science Field

Intro to Data and Data Science – Common Data Science Techniques

Traditional Data: Techniques
Traditional Data: Real-life Examples
Big Data: Techniques
Big Data: Techniques
Big Data: Real-life Examples
Business Intelligence (BI): Techniques
Business Intelligence (BI): Techniques
Business Intelligence (BI): Real-life Examples
Traditional Methods: Techniques
Traditional Methods: Techniques
Traditional Methods: Real-life Examples
Machine Learning (ML): Techniques
Machine Learning (ML): Techniques
Machine Learning (ML): Types of Machine Learning
Machine Learning (ML): Types of Machine Learning
Machine Learning (ML): Real-life Examples
Machine Learning (ML): Real-life Examples

Intro to Data and Data Science – Common Data Science Tools

Intro to Data and Data Science – Data Science Career Paths

Intro to Data and Data Science – Dispelling Common Misconceptions

Part 2: Statistics – Population and Sample

Statistics – Descriptive Statistics

Types of data
Levels of Measurement
Levels of measurement
Categorical Variables – Visualization Techniques
Categorical variables. Visualization Techniques
Categorical Variables Exercise
Numerical Variables – Frequency Distribution Table
Numerical variables. Using a frequency distribution table
Numerical Variables Exercise
The Histogram
The Histogram
Histogram Exercise
Cross Table and Scatter Plot
Cross Tables and Scatter Plots
Cross Tables and Scatter Plots Exercise
Mean, median and mode
Mean, Median and Mode Exercise
Skewness
Skewness
Skewness Exercise
Variance
Variance Exercise
Standard Deviation and Coefficient of Variation
Standard deviation
Standard Deviation and Coefficient of Variation Exercise
Covariance
Covariance
Covariance Exercise
Correlation Coefficient
Correlation Coefficient
Correlation Coefficient Exercise
Test 1
Test 2
Test 3

Statistics – Practical Example: Descriptive Statistics

Statistics – Inferential Statistics Fundamentals

What is a Distribution
What is a Distribution
The Normal Distribution
The Normal Distribution
The Standard Normal Distribution
The Standard Normal Distribution
The Standard Normal Distribution Exercise
Central Limit Theorem
Central Limit Theorem
Standard error
Standard error
Estimators and Estimates
Estimators and Estimates
Central Limit Theorem
The Normal Distribution
What is a Distribution
The Standard Normal Distribution Exercise

Statistics – Inferential Statistics: Confidence Intervals

What are Confidence Intervals?
Confidence Intervals; Population Variance Known; z-score
Confidence Intervals; Population Variance Known; z-score Exercise
Confidence interval clarifications
Student’s T Distribution
Student’s T Distribution
Confidence Intervals; Population Variance Unknown; t-score
Confidence Intervals; Population Variance Unknown; t-score Exercise
Margin of Error
Margin of Error
Confidence intervals. Two means. Dependent samples
Confidence intervals. Two means. Dependent samples Exercise
Confidence intervals. Two means. Independent samples (Part 1)
Confidence intervals. Two means. Independent samples (Part 1) Exercise
Confidence intervals. Two means. Independent samples (Part 2)
Confidence intervals. Two means. Independent samples (Part 2) Exercise
Confidence intervals. Two means. Independent samples (Part 3)
Confidence Intervals; Population Variance Known; z-score
Confidence intervals. Two means. Dependent samples

Statistics – Practical Example: Inferential Statistics

Statistics – Hypothesis Testing

Further Reading on Null and Alternative Hypothesis
The Null vs Alternative Hypothesis
Rejection Region and Significance Level
Rejection Region and Significance Level
Type I Error and Type II Error
Type I Error and Type II Error
Test for the Mean. Population Variance Known
Test for the Mean. Population Variance Known Exercise
p-value
p-value
Test for the Mean. Population Variance Unknown
Test for the Mean. Population Variance Unknown Exercise
Test for the Mean. Dependent Samples
Test for the Mean. Dependent Samples Exercise
Test for the mean. Independent samples (Part 1)
Test for the mean. Independent samples (Part 1). Exercise
Test for the mean. Independent samples (Part 2)
Test for the mean. Independent samples (Part 2)
Test for the mean. Independent samples (Part 2)
Test 1
Test 2
Test 3

Statistics – Practical Example: Hypothesis Testing

Part 3: Relational Database Theory & Introduction to SQL

Why use SQL?
Why use MySQL?
Why use MySQL?
Introducing Databases
Introducing Databases
Relational Database Fundamentals
Relational Database Fundamentals
Comparing Databases and Spreadsheets
Important Database Terminology
Important Database Terminology
The Concept of Relational Schemas: Primary Key
The Concept of Relational Schemas: Primary Key
The Concept of Relational Schemas: Foreign Key
The Concept of Relational Schemas: Foreign Key
The Concept of Relational Schemas: Unique Key and Null Values
The Concept of Relational Schemas: Unique Key
The Concept of Relational Schemas: Relationships Between Tables
The Concept of Relational Schemas: Relationships Between Tables

SQL – Install and get to know MySQL

Installing Visual C
Installing MySQL on macOS and Unix systems
The Client-Server Model
Linking GUI with the MySQL Server
Read me!!!
Creating a New User and a New Connection to it
Familiarize Yourself with the MySQL Interface
SQL Fundamentals – MySQL Session and Databases
SQL Fundamentals – DROP, CREATE, SELECT, INSERT, DELETE
Installing MySQL on macOS and Unix systems
Creating a New User and a New Connection to it
SQL Fundamentals – MySQL Session and Databases

SQL – Best SQL Practices

SQL – Loading the ’employees’ Database

SQL – Practical Application of the SQL SELECT Statement

Using SELECT – FROM – Exercise
Using SELECT – FROM – Solution
Using WHERE
Using WHERE – Exercise
Using WHERE – Solution
Using AND
Using AND – Exercise
Using AND – Solution
Using OR
Using OR – Exercise
Using OR – Solution
Operator Precedence and Logical Order
Operator Precedence and Logical Order – Exercise
Operator Precedence and Logical Order – Solution
Using IN – NOT IN
Using IN – NOT IN – Exercise 1
Using IN – NOT IN – Solution 1
Using IN – NOT IN – Exercise 2
Using IN – NOT IN – Solution 2
Using LIKE – NOT LIKE
Using LIKE – NOT LIKE – Exercise
Using LIKE – NOT LIKE – Solution
Using Wildcard Characters
Using Wildcard characters – Exercise
Using Wildcard characters – Solution
Using BETWEEN – AND
Using BETWEEN – AND – Exercise
Using BETWEEN – AND – Solution
Using IS NOT NULL – IS NULL
Using IS NOT NULL – IS NULL – Exercise
Using IS NOT NULL – IS NULL – Solution
Using Other Comparison Operators
Using Other Comparison Operators – Exercise
Using Other Comparison Operators – Solution
Using SELECT DISTINCT
Using SELECT DISTINCT – Exercise
Using SELECT DISTINCT – Solution
Getting to Know Aggregate Functions
Getting to Know Aggregate Functions – Exercise
Getting to Know Aggregate Functions – Solution
Using ORDER BY
Using ORDER BY – Exercise
Using ORDER BY – Solution
Using GROUP BY
Using Aliases (AS)
Using Aliases (AS) – Exercise
Using Aliases (AS) – Solution
Using HAVING
Using HAVING – Exercise
Using HAVING – Solution
Using WHERE vs HAVING – Part I
Using WHERE vs HAVING – Part II
Using WHERE vs HAVING – Part II – Exercise
Using WHERE vs HAVING – Part II – Solution
Using LIMIT
Using LIMIT – Exercise
Using LIMIT – Solution

SQL – Expanding on MySQL Aggregate Functions

Applying COUNT() – Exercise
Applying COUNT() – Solution
Applying SUM()
Applying SUM() – Exercise
Applying SUM() – Solution
MIN() and MAX()
MIN() and MAX() – Exercise
MIN() and MAX() – Solution
Applying AVG()
Applying AVG() – Exercise
Applying AVG() – Solution
Rounding Numbers with ROUND()
Rounding Numbers with ROUND() – Exercise
Rounding Numbers with ROUND() – Solution

SQL – SQL JOINs

What are JOINs? – Exercise 1
What are JOINs? – Exercise 2
What are JOINs? – Exercise 3
What are JOINs? – Exercise 4
What are JOINs? – Exercise 5
The Functionality of INNER JOIN – Part I
The Functionality of INNER JOIN – Part II
The Functionality of INNER JOIN – PART II – Exercise
The Functionality of INNER JOIN – PART II – Solution
Extra Info on Using Joins
Duplicate Rows
The Functionality of LEFT JOIN – Part I
The Functionality of LEFT JOIN – Part II
The Functionality of LEFT JOIN – Part II – Exercise
The Functionality of LEFT JOIN – Part II – Solution
The Functionality of RIGHT JOIN
Differences between the New and the Old Join Syntax
Differences between the New and the Old Join Syntax – Exercise
Differences between the New and the Old Join Syntax – Solution
Using JOIN and WHERE Together
Important – Prevent Error Code: 1055!
Using JOIN and WHERE Together – Exercise
Using JOIN and WHERE Together – Solution
The Functionality of CROSS JOIN
The Functionality of CROSS JOIN – Exercise 1
The Functionality of CROSS JOIN – Solution 1
The Functionality of CROSS JOIN – Exercise 2
The Functionality of CROSS JOIN – Solution 2
Combining Aggregate Functions with Joins
JOIN More than Two Tables
JOIN More than Two Tables – Exercise
JOIN More than Two Tables – Solution
Top Tips for Joins
Top Tips for Joins – Exercise
Top Tips for Joins – Solution
The Differences Between UNION and UNION ALL
The Differences Between UNION and UNION ALL – Exercise
The Differences Between UNION and UNION ALL – Solution

SQL – SQL Subqueries

SQL Subqueries with IN Embedded Inside WHERE – Exercise
SQL Subqueries with IN Embedded Inside WHERE – Solution
SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE
SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE – Exercise
SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE – Solution
SQL Subqueries Nested in SELECT and FROM
SQL Subqueries Embedded in SELECT and FROM – Exercise 1
SQL Subqueries Embedded in SELECT and FROM – Exercise 2
SQL Subqueries Nested in SELECT and FROM – Solution 2

SQL – Stored Routines

Defining Stored Routines
Create Stored Procedures with MySQL Syntax
An Example of Stored Procedures Part I
An Example of Stored Procedures Part II
An Example of Stored Procedures Part II – Exercise
An Example of Stored Procedures Part II – Solution
Creating a Procedure in MySQL Another Way
Create Stored Procedures with an Input Parameter
Create Stored Procedures with an Output Parameter
Create Stored Procedures with an Output Parameter – Exercise
Stored Procedures with an Output Parameter – Solution
SQL Variables
SQL Variables – Exercise
SQL Variables – Solution
The Benefit of User-Defined Functions in MySQL
Error Code: 1418.
The Benefit of User-Defined Functions in MySQL – Exercise
The Benefit of User-Defined Functions in MySQL – Solution
Concluding Stored Routines
Concluding Stored Routines

SQL – The CASE Statement

SQL – Window Functions

The ROW_NUMBER() Ranking Window Function and the Relevant MySQL Syntax
The ROW_NUMBER Ranking Window Function – Exercise
The ROW_NUMBER Ranking Window Function – Solution
A Note on Using Several Window Functions in a Query
A Note on Using Several Window Functions in a Query – Exercise
A Note on Using Several Window Functions in a Query – Solution
MySQL Window Functions Syntax
MySQL Window Functions Syntax – Exercise
MySQL Window Functions Syntax – Solution
The PARTITION BY Clause vs the GROUP BY Clause
The PARTITION BY Clause vs the GROUP BY Clause – Exercise
The PARTITION BY Clause vs the GROUP BY Clause – Solution
The MySQL RANK() and DENSE_RANK() Window Functions
The MySQL RANK() and DENSE_RANK() Window Functions – Exercise
The MySQL RANK() and DENSE_RANK() Window Functions – Solution
Working with MySQL Ranking Window Functions and Joins Together
Working with MySQL Ranking Window Functions and Joins Together – Exercise
Working with MySQL Ranking Window Functions and Joins Together – Solution
The LAG() and LEAD() Value Window Functions
The LAG() and LEAD() Value Window Functions – Exercise
The LAG() and LEAD() Value Window Functions – Solution
MySQL Aggregate Functions in the Context of Window Functions – Part I
MySQL Aggregate Functions in the Context of Window Functions – Part I-Exercise
MySQL Aggregate Functions in the Context of Window Functions – Part I-Solution
MySQL Aggregate Functions in the Context of Window Functions – Part II
MySQL Aggregate Functions in the Context of Window Functions – Part II-Exercise
MySQL Aggregate Functions in the Context of Window Functions – Part II-Solution

SQL Common Table Expressions (CTEs)

SQL Temporary Tables

Part 4: Introduction to Tableau

Tableau – Tableau functionalities

Tableau – The Tableau Exercise

Let’s Create a Dashboard – Visualizing the Three Charts We Want to Create
Using Joins in Tableau
Performing a Numbers Check – Attempt #1
Blending Data in Tableau
Performing a Numbers Check – Attempt #2
First Chart
Second Chart
Third Chart
Creating and Formatting a Dashboard
Adding Interactive Filters for Improved Analysis
Interactive Filters – fix
Using Joins in Tableau

Part 5: Combining SQL and Tableau – Introduction

Combining SQL and Tableau – Problem 1

Combining SQL and Tableau – Problem 2

Combining SQL and Tableau – Problem 3

Combining SQL and Tableau – Problem 4

Part 6: Introduction to Programming with Python

A 5-minute explanation of Programming
Why use Python?
Why Use Python?
Why use Jupyter?
Why Use Jupyter?
How to Install Python and Jupyter
Understanding Jupyter’s Interface – Dashboard
Understanding Jupyter’s Interface – Prerequisites for Coding
Understanding Jupyter’s Interface
Python 2 vs Python 3

Python – Python Variables and Data Types

Python Variables – Exercise #1
Python Variables – Exercise #2
Python Variables – Exercise #3
Python Variables – Exercise #4
Python Variables
Understanding Numbers and Boolean Values
Numbers and Boolean Values – Exercise #1
Numbers and Boolean Values – Exercise #2
Numbers and Boolean Values – Exercise #3
Numbers and Boolean Values – Exercise #4
Numbers and Boolean Values – Exercise #5
Understanding Numbers and Boolean Values

00:00
Strings
Strings – Exercise #1
Strings – Exercise #2
Strings – Exercise #3
Strings – Exercise #4
Strings – Exercise #5
Strings

Python – Python Syntax Fundamentals

The Arithmetic Operators in Python – Exercise #1
The Arithmetic Operators in Python – Exercise #2
The Arithmetic Operators in Python – Exercise #3
The Arithmetic Operators in Python – Exercise #4
The Arithmetic Operators in Python – Exercise #5
The Arithmetic Operators in Python – Exercise #6
The Arithmetic Operators in Python – Exercise #7
The Arithmetic Operators in Python – Exercise #8
Using Arithmetic Operators in Python
What is the Double Equality Sign?
What is the Double Equality Sign? – Exercise #1
What is the Double Equality Sign?
How to Reassign Values
How to Reassign Values – Exercise #1
How to Reassign Values – Exercise #2
How to Reassign Values – Exercise #3
How to Reassign Values – Exercise #4
How to Reassign Values
How to Add Comments
How to Add Comments
Understanding Line Continuation
Understanding Line Continuation – Exercise #1
How to Index Elements
How to Index Elements – Exercise #1
How to Index Elements – Exercise #2
How to Index Elements
How to Structure Your Code with Indentation
How to Structure Your Code with Indentation – Exercise #1
How to Structure Your Code with Indentation

Python – Other Python Operators

Python’s Comparison Operators – Exercise #1
Python’s Comparison Operators – Exercise #2
Python’s Comparison Operators – Exercise #3
Python’s Comparison Operators – Exercise #4
Python’s Comparison Operators
Python’s Logical and Identity Operators
Python’s Logical and Identity Operators – Exercise #1
Python’s Logical and Identity Operators – Exercise #2
Python’s Logical and Identity Operators – Exercise #3
Python’s Logical and Identity Operators – Exercise #4
Python’s Logical and Identity Operators – Exercise #5
Python’s Logical and Identity Operators – Exercise #6
Python’s Logical and Identity Operators

Python – Conditional Statements

The IF Statement – Exercise #1
The IF Statement – Exercise #2
Getting to know the IF Statement
Adding an ELSE statement
The ELSE Statement – Exercise #1
Else if, for Brief – ELIF
The ELIF Statement – Exercise #1
The ELIF Statement – Exercise #2
An Additional Explanation of Boolean Values
An Additional Explanation of Boolean Values

Python – Functions

How to Create a Function with a Parameter
How to Create a Function with a Parameter – Exercise #1
How to Create a Function with a Parameter – Exercise #2
Define a Function in Another Way
Define a Function in Another Way – Exercise #1
How to Use a Function within a Function
How to Use a Function within a Function – Exercise #1
Use Conditional Statements and Functions Together
Conditional Statements and Functions – Exercise #1
How to Create Functions Which Contain a Few Arguments
Built-In Functions in Python Worth Knowing
Built-In Function in Python Worth Knowing – Exercise #1
Built-In Function in Python Worth Knowing – Exercise #2
Built-In Function in Python Worth Knowing – Exercise #3
Built-In Function in Python Worth Knowing – Exercise #4
Built-In Function in Python Worth Knowing – Exercise #5
Built-In Function in Python Worth Knowing – Exercise #6
Built-In Function in Python Worth Knowing – Exercise #7
Built-In Function in Python Worth Knowing – Exercise #8
Built-In Function in Python Worth Knowing – Exercise #9
Python – Functions
Test 1

Python – Python Sequences

Introduction to Lists – Exercise #1
Introduction to Lists – Exercise #2
Introduction to Lists – Exercise #3
Introduction to Lists – Exercise #4
Introduction to Lists – Exercise #5
Introduction to Lists
Using Methods in Python
Using Methods in Python – Exercise #1
Using Methods in Python – Exercise #2
Using Methods in Python – Exercise #3
Using Methods in Python – Exercise#4
Using Methods in Python
What is List Slicing?
What is List Slicing? – Exercise #1
What is List Slicing? – Exercise #2
What is List Slicing? – Exercise #3
What is List Slicing? – Exercise #4
What is List Slicing? – Exercise #5
What is List Slicing? – Exercise #6
What is List Slicing? – Exercise #7
Working with Tuples
Working with Tuples – Exercise #1
Working with Tuples – Exercise #2
Working with Tuples – Exercise #3
Working with Tuples – Exercise #4
Python Dictionaries
Python Dictionaries – Exercise #1
Python Dictionaries – Exercise #2
Python Dictionaries – Exercise #3
Python Dictionaries – Exercise #4
Python Dictionaries – Exercise #5
Python Dictionaries – Exercise #6
Python Dictionaries

Python – Using Iterations

Using For Loops – Exercise #1
Using For Loops – Exercise #2
Using For Loops
Using While Loops and Incrementing
Using While Loops and Incrementing – Exercise #1
Use the range() Function to Create Lists
Use the range() Function to Create Lists – Exercise – #1
Use the range() Function to Create Lists – Exercise – #2
Use the range() Function to Create Lists – Exercise – #3
Use the range() Function to Create Lists
Combine Conditional Statements and Loops
Conditional Statements and Loops – Exercise #1
Conditional Statements and Loops – Exercise #2
Conditional Statements and Loops – Exercise #3
All In – Conditional Statements, Functions, and Loops
All In – Conditional Statements, Functions, and Loops – Exercise #1
How to Iterate over Dictionaries
How to Iterate over Dictionaries – Exercise #1
How to Iterate over Dictionaries – Exercise #2

Python – Advanced Python tools

Part 7: Integration – Software Integration

Getting Started with Data, Servers, Clients, Requests, and Responses
Getting Started with Data Connectivity, APIs, and Endpoints
Getting Started with Data Connectivity, APIs, and Endpoints
Become Better Acquainted with APIs
Become Better Acquainted with APIs
Communication through Text Files
Communication through Text Files
What is Software Integration and How is it Applied?
What is Software Integration and How is it Applied?
Become Better Acquainted with APIs

Integration – What is contained in this Course?

Integration – Data Preprocessing Step by Step

How to Import the Data Set in Python
Exploring the Data Set
Programming vs the Rest of the World
A Brief Summary of Regression Analysis
The Approach we will Take to Solve this Exercise
Dropping Variables We Don’t Need
EXERCISE – Dropping Variables We Don’t Need
SOLUTION – Dropping Variables We Don’t Need
A Deeper Look at the ‘Reasons for Absence’ Column
Splitting a Variable into Multiple Dummy Variables
SOLUTION – Splitting a Variable into Multiple Dummy Variables
How to Drop a Dummy Variable from the Data Set
A Statistical Perspective on Dummy Variables
Categorizing the Various Reasons for Absence
Concatenation in Python
EXERCISE – Concatenation in Python
SOLUTION – Concatenation in Python
How to Reorder Columns in a DataFrame in Python
EXERCISE – How to Reorder Columns in a DataFrame in Python
SOLUTION – How to Reorder Columns in a DataFrame in Python
Using Checkpoints to Ease Your Work in Jupyter
EXERCISE – Using Checkpoints to Ease Your Work in Jupyter
SOLUTION – Using Checkpoints to Ease Your Work in Jupyter
Analyzing the “Date” Column
Retrieving the Month Value From the “Date” Column
Adding the “Day of the Week” Column
EXERCISE – Dropping Columns
Analysis of the Next 5 Columns in DF
Dealing with More Numerical Features which may Behave like Categorical Ones
A Final Note on this Section
Programming vs the Rest of the World

Integration – Integrating Python and SQL

How to Use the ‘absenteeism_module’ in Python – Part II
Creating the ‘predicted_outputs’ Database in MySQL
Importing ‘pymysql’ in Python
Creating a Connection and Cursor
EXERCISE – Creating ‘df_new_obs’
Creating the ‘predicted_outputs’ Table in MySQL
Executing and SQL SELECT Statement from Python
Sending Data from Jupyter to Workbench – Part I
Sending Data from Jupyter to Workbench – Part II
Sending Data from Jupyter to Workbench – Part III

Integration – Using Tableau to Analyze the Predicted Outputs

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