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Business Analysis
Business
Business Analytics & Intelligence
The Business Intelligence Analyst Course 2024
The skills you need to become a BI Analyst - Statistics, Database theory, SQL, Tableau – Everything is included
4.6
(48293)
251124 enrolled on this course
Last updated 11/2021
365 Careers
Description
Hi! Welcome to The Business Intelligence Analyst Course, the only course you need to become a BI Analyst.
We are proud to present you 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.
Our program is different than the rest of the materials available online.
It is truly comprehensive. The Business Intelligence Analyst Course comprises of 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. And today, you have the chance of acquiring an invaluable advantage to get ahead of other candidates. This course will be the secret to your success. And your success is our 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 out there. 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
Learning a programming language is meaningless without putting it to use. That’s why we
integrate SQL and Tableau
, and perform several real-life Business Intelligence tasks
Sounds amazing, right?
Our courses are unique because our team works hard to:
Script the entire content
Work with real-life examples
Provide easy to understand and complete explanations
Create beautiful and engaging animations
Prepare exercises, course notes, quizzes, and other materials that will enhance your course taking experience
Be there for you and provide support whenever necessary
We love teaching and we are really excited about this journey. It will get your foot in the door of an exciting and rising profession. Don’t hesitate and enrol today. The only regret you will have is that you didn’t find this course sooner!
Who this course is for:
Beginners to programming and data science
Students eager to learn about job opportunities in the field of data science
Candidates willing to boost their resume by learning how to combine the knowledge of Statistics, SQL, and Tableau in a real-world working environment
SQL Programmers who want to develop business reasoning and apply their knowledge to the solution of various business tasks
People interested in a Business Intelligence Analyst career
What you'll learn
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
Requirements
- You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
- No previous design experience is needed.
- No previous Adobe XD skills are needed.
Course Content
27 sections • 95 lectures
Expand All Sections
1.1-What Does the Course Cover
1.2-Download All Resources
2.1-Why Are There So Many Business and Data Science Buzzwords?
2.2-Analysis vs Analytics
2.3-Intro to Business Analytics, Data Analytics, and Data Science
2.4-Intro to Business Analytics, Data Analytics, and Data Science
2.5-Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture
2.6-Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture
2.7-An Overview of our Data Science Infographic
2.8-An Overview of our Data Science Infographic
3.1-When are Traditional data, Big Data, BI, Traditional Data Science and ML applied
3.2-When are Traditional data, Big Data, BI, Traditional Data Science and ML applied
4.1-Why do we Need each of these Disciplines?
4.2-Why do we Need each of these Disciplines?
5.1-Traditional Data: Techniques
5.2-Traditional Data: Techniques
5.3-Traditional Data: Real-life Examples
5.4-Big Data: Techniques
5.5-Big Data: Techniques
5.6-Big Data: Real-life Examples
5.7-Business Intelligence (BI): Techniques
5.8-Business Intelligence (BI): Techniques
5.9-Business Intelligence (BI): Real-life Examples
5.10-Traditional Methods: Techniques
5.11-Traditional Methods: Techniques
5.12-Traditional Methods: Real-life Examples
5.13-Machine Learning (ML): Techniques
5.14-Machine Learning (ML): Techniques
5.15-Machine Learning (ML): Types of Machine Learning
5.16-Machine Learning (ML): Types of Machine Learning
5.17-Machine Learning (ML): Real-life Examples
5.18-Machine Learning (ML): Real-life Examples
6.1-Programming Languages & Software Employed in Data Science - All the Tools Needed
6.2-Programming Languages & Software Employed in Data Science - All the Tools Needed
7.1-Data Science Job Positions: What do they Involve and What to Look out for?
7.2-Data Science Job Positions: What do they Involve and What to Look out for?
8.1-Dispelling common Misconceptions
8.2-Dispelling common Misconceptions
9.1-Population vs sample
9.2-Population and Sample
10.1-Types of Data
10.2-Types of data
10.3-Levels of Measurement
10.4-Levels of measurement
10.5-Categorical Variables - Visualization Techniques
10.6-Categorical variables. Visualization Techniques
10.7-Categorical Variables Exercise
10.8-Numerical Variables - Frequency Distribution Table
10.9-Numerical variables. Using a frequency distribution table
10.10-Numerical Variables Exercise
10.11-The Histogram
10.12-The Histogram
10.13-Histogram Exercise
10.14-Cross Table and Scatter Plot
10.15-Cross Tables and Scatter Plots
10.16-Cross Tables and Scatter Plots Exercise
10.17-Mean, median and mode
10.18-Mean, Median and Mode Exercise
10.19-Skewness
10.20-Skewness
10.21-Skewness Exercise
10.22-Variance
10.23-Variance Exercise
10.24-Standard Deviation and Coefficient of Variation
10.25-Standard deviation
10.26-Standard Deviation and Coefficient of Variation Exercise
10.27-Covariance
10.28-Covariance
10.29-Covariance Exercise
10.30-Correlation Coefficient
10.31-Correlation Coefficient
10.32-Correlation Coefficient Exercise
11.1-Practical Example
11.2-Practical Example Exercise
12.1-Introduction
12.2-What is a Distribution
12.3-What is a Distribution
12.4-The Normal Distribution
12.5-The Normal Distribution
12.6-The Standard Normal Distribution
12.7-The Standard Normal Distribution
12.8-The Standard Normal Distribution Exercise
12.9-Central Limit Theorem
12.10-Central Limit Theorem
12.11-Standard error
12.12-Standard error
12.13-Estimators and Estimates
12.14-Estimators and Estimates
13.1-What are Confidence Intervals?
13.2-What are Confidence Intervals?
13.3-Confidence Intervals
Population Variance Known
z-score
13.4-Confidence Intervals
Population Variance Known
z-score Exercise
13.5-Confidence interval clarifications
13.6-Student's T Distribution
13.7-Student's T Distribution
13.8-Confidence Intervals
Population Variance Unknown
t-score
13.9-Confidence Intervals
Population Variance Unknown
t-score Exercise
13.10-Margin of Error
13.11-Margin of Error
13.12-Confidence intervals. Two means. Dependent samples
13.13-Confidence intervals. Two means. Dependent samples Exercise
13.14-Confidence intervals. Two means. Independent samples (Part 1)
13.15-Confidence intervals. Two means. Independent samples (Part 1) Exercise
13.16-Confidence intervals. Two means. Independent samples (Part 2)
13.17-Confidence intervals. Two means. Independent samples (Part 2) Exercise
13.18-Confidence intervals. Two means. Independent samples (Part 3)
14.1-Practical Example: Inferential Statistics
14.2-Practical Example: Inferential Statistics Exercise
15.1-The Null vs Alternative Hypothesis
15.2-Further Reading on Null and Alternative Hypothesis
15.3-The Null vs Alternative Hypothesis
15.4-Rejection Region and Significance Level
15.5-Rejection Region and Significance Level
15.6-Type I Error and Type II Error
15.7-Type I Error and Type II Error
15.8-Test for the Mean. Population Variance Known
15.9-Test for the Mean. Population Variance Known Exercise
15.10-p-value
15.11-p-value
15.12-Test for the Mean. Population Variance Unknown
15.13-Test for the Mean. Population Variance Unknown Exercise
15.14-Test for the Mean. Dependent Samples
15.15-Test for the Mean. Dependent Samples Exercise
15.16-Test for the mean. Independent samples (Part 1)
15.17-Test for the mean. Independent samples (Part 1). Exercise
15.18-Test for the mean. Independent samples (Part 2)
15.19-Test for the mean. Independent samples (Part 2)
15.20-Test for the mean. Independent samples (Part 2)
16.1-Practical Example: Hypothesis Testing
16.2-Practical Example: Hypothesis Testing Exercise
17.1-Why use SQL?
17.2-Why use SQL?
17.3-Why use MySQL?
17.4-Why use MySQL?
17.5-Introducing Databases
17.6-Introducing Databases
17.7-Relational Database Fundamentals
17.8-Relational Database Fundamentals
17.9-Comparing Databases and Spreadsheets
17.10-Comparing Databases and Spreadsheets
17.11-Important Database Terminology
17.12-Important Database Terminology
17.13-The Concept of Relational Schemas: Primary Key
17.14-The Concept of Relational Schemas: Primary Key
17.15-The Concept of Relational Schemas: Foreign Key
17.16-The Concept of Relational Schemas: Foreign Key
17.17-The Concept of Relational Schemas: Unique Key and Null Values
17.18-The Concept of Relational Schemas: Unique Key
17.19-The Concept of Relational Schemas: Relationships Between Tables
17.20-The Concept of Relational Schemas: Relationships Between Tables
18.1-Installing MySQL Workbench and Server
18.2-Installing Visual C
18.3-Installing MySQL on macOS and Unix systems
18.4-The Client-Server Model
18.5-Linking GUI with the MySQL Server
18.6-Read me!!!
18.7-Creating a New User and a New Connection to it
18.8-Familiarize Yourself with the MySQL Interface
18.9-SQL Fundamentals - MySQL Session and Databases
18.10-SQL Fundamentals - DROP, CREATE, SELECT, INSERT, DELETE
19.1-Coding Tips and Best Practices - I
19.2-Coding Tips and Best Practices - I
19.3-Coding Tips and Best Practices - II
19.4-Coding Tips and Best Practices - II
20.1-Loading the 'employees' Database
20.2-Loading the 'employees' Database
21.1-Using SELECT - FROM
21.2-Using SELECT - FROM - Exercise
21.3-Using SELECT - FROM - Solution
21.4-CODING EXERCISES - the 'employees_10' Database
21.5-SELECT - FROM - Exercise #1
21.6-SELECT - FROM - Exercise #2
21.7-SELECT - FROM - Exercise #3
21.8-SELECT - FROM - Exercise #4
21.9-Using WHERE
21.10-Using WHERE - Exercise
21.11-Using WHERE - Solution
21.12-SELECT - Using WHERE - Exercise #1
21.13-Using AND
21.14-Using AND - Exercise
21.15-Using AND - Solution
21.16-SELECT - Using AND - Exercise #1
21.17-Using OR
21.18-Using OR - Exercise
21.19-Using OR - Solution
21.20-SELECT - Using OR - Exercise #1
21.21-Operator Precedence and Logical Order
21.22-Operator Precedence and Logical Order - Exercise
21.23-Operator Precedence and Logical Order - Solution
21.24-Operator Precedence and Logical Order - Exercise #1
21.25-Using IN - NOT IN
21.26-Using IN - NOT IN - Exercise 1
21.27-Using IN - NOT IN - Solution 1
21.28-Using IN - NOT IN - Exercise 2
21.29-Using IN - NOT IN - Solution 2
21.30-SELECT - Using IN - NOT IN - Exercise #1
21.31-SELECT - Using IN - NOT IN - Exercise #2
21.32-Using LIKE - NOT LIKE
21.33-Using LIKE - NOT LIKE - Exercise
21.34-Using LIKE - NOT LIKE - Solution
21.35-SELECT - Using LIKE - NOT LIKE - Exercise #1
21.36-SELECT - Using LIKE - NOT LIKE - Exercise #2
21.37-SELECT - Using LIKE - NOT LIKE - Exercise #3
21.38-Using Wildcard Characters
21.39-Using Wildcard characters - Exercise
21.40-Using Wildcard characters - Solution
21.41-Using Wildcard characters - Exercise #1
21.42-Using Wildcard characters - Exercise #2
21.43-Using BETWEEN - AND
21.44-Using BETWEEN - AND - Exercise
21.45-Using BETWEEN - AND - Solution
21.46-SELECT - Using BETWEEN - AND - Exercise #1
21.47-SELECT - Using BETWEEN - AND - Exercise #2
21.48-SELECT - Using BETWEEN - AND - Exercise #3
21.49-Using IS NOT NULL - IS NULL
21.50-Using IS NOT NULL - IS NULL - Exercise
21.51-Using IS NOT NULL - IS NULL - Solution
21.52-SELECT - Using IS NOT NULL - IS NULL - Exercise #1
21.53-Using Other Comparison Operators
21.54-Using Other Comparison Operators - Exercise
21.55-Using Other Comparison Operators - Solution
21.56-SELECT - Using Other Comparison Operators - Exercise #1
21.57-SELECT - Using Other Comparison Operators - Exercise #2
21.58-Using SELECT DISTINCT
21.59-Using SELECT DISTINCT - Exercise
21.60-Using SELECT DISTINCT - Solution
21.61-SELECT DISTINCT - Exercise #2
21.62-Getting to Know Aggregate Functions
21.63-Getting to Know Aggregate Functions - Exercise
21.64-Getting to Know Aggregate Functions - Solution
21.65-Getting to Know Aggregate Functions - Exercise #1
21.66-Getting to Know Aggregate Functions - Exercise #2
21.67-Using ORDER BY
21.68-Using ORDER BY - Exercise
21.69-Using ORDER BY - Solution
21.70-SELECT - Using ORDER BY - Exercise #1
21.71-Using GROUP BY
21.72-Using Aliases (AS)
21.73-Using Aliases (AS) - Exercise
21.74-Using Aliases (AS) - Solution
21.75-SELECT - Using Aliases (AS) - Exercise #1
21.76-Using HAVING
21.77-Using HAVING - Exercise
21.78-Using HAVING - Solution
21.79-SELECT - Using HAVING - Exercise #1
21.80-Using WHERE vs HAVING - Part I
21.81-Using WHERE vs HAVING - Part II
21.82-Using WHERE vs HAVING - Part II - Exercise
21.83-Using WHERE vs HAVING - Part II - Solution
21.84-SELECT - Using WHERE vs HAVING - Exercise #1
21.85-Using LIMIT
21.86-Using LIMIT - Exercise
21.87-Using LIMIT - Solution
21.88-SELECT - Using LIMIT - Exercise #1
22.1-Applying COUNT()
22.2-Applying COUNT() - Exercise
22.3-Applying COUNT() - Solution
22.4-Applying COUNT() - Exercise #1
22.5-Applying SUM()
22.6-Applying SUM() - Exercise
22.7-Applying SUM() - Solution
22.8-Applying SUM() - Exercise #1
22.9-MIN() and MAX()
22.10-MIN() and MAX() - Exercise
22.11-MIN() and MAX() - Solution
22.12-MIN() and MAX() - Exercise #1
22.13-MIN() and MAX() - Exercise #2
22.14-Applying AVG()
22.15-Applying AVG() - Exercise
22.16-Applying AVG() - Solution
22.17-Applying AVG() - Exercise #1
22.18-Rounding Numbers with ROUND()
22.19-Rounding Numbers with ROUND() - Exercise
22.20-Rounding Numbers with ROUND() - Solution
22.21-Applying ROUND() - Exercise #1
23.1-What are JOINs?
23.2-What are JOINs? - Exercise 1
23.3-What are JOINs? - Exercise 2
23.4-The Functionality of INNER JOIN - Part I
23.5-The Functionality of INNER JOIN - Part II
23.6-The Functionality of INNER JOIN - PART II - Exercise
23.7-The Functionality of INNER JOIN - PART II - Solution
23.8-INNER JOIN - Exercise #1
23.9-Extra Info on Using Joins
23.10-Duplicate Rows
23.11-The Functionality of LEFT JOIN - Part I
23.12-The Functionality of LEFT JOIN - Part II
23.13-The Functionality of LEFT JOIN - Part II - Exercise
23.14-The Functionality of LEFT JOIN - Part II - Solution
23.15-LEFT JOIN - Exercise #1
23.16-The Functionality of RIGHT JOIN
23.17-RIGHT JOIN - Exercise #1
23.18-Differences between the New and the Old Join Syntax
23.19-Differences between the New and the Old Join Syntax - Exercise
23.20-Differences between the New and the Old Join Syntax - Solution
23.21-Differences between the New and the Old Join Syntax - Exercise #1
23.22-Using JOIN and WHERE Together
23.23-Important – Prevent Error Code: 1055!
23.24-Using JOIN and WHERE Together - Exercise
23.25-Using JOIN and WHERE Together - Solution
23.26-Using JOIN and WHERE Together - Exercise #1
23.27-The Functionality of CROSS JOIN
23.28-The Functionality of CROSS JOIN - Exercise 1
23.29-The Functionality of CROSS JOIN - Solution 1
23.30-The Functionality of CROSS JOIN - Exercise 2
23.31-The Functionality of CROSS JOIN - Solution 2
23.32-The Functionality of CROSS JOIN - Exercise #1
23.33-The Functionality of CROSS JOIN - Exercise #2
23.34-Combining Aggregate Functions with Joins
23.35-JOIN More than Two Tables
23.36-JOIN More than Two Tables - Exercise
23.37-JOIN More than Two Tables - Solution
23.38-JOIN More than Two Tables - Exercise #1
23.39-Top Tips for Joins
23.40-Top Tips for Joins - Exercise
23.41-Top Tips for Joins - Solution
23.42-Top Tips for Joins - Exercise #1
23.43-The Differences Between UNION and UNION ALL
23.44-The Differences Between UNION and UNION ALL - Exercise
23.45-The Differences Between UNION and UNION ALL - Solution
23.46-The Differences Between UNION and UNION ALL - Exercise #1
24.1-SQL Subqueries with IN Embedded Inside WHERE
24.2-SQL Subqueries with IN Embedded Inside WHERE - Exercise
24.3-SQL Subqueries with IN Embedded Inside WHERE - Solution
24.4-SQL Subqueries with IN Embedded Inside WHERE - Exercise #1
24.5-SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE
24.6-SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE - Exercise
24.7-SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE - Solution
24.8-SQL Subqueries with EXISTS-NOT EXISTS Embedded Inside WHERE - Exercise #1
24.9-SQL Subqueries Nested in SELECT and FROM
24.10-SQL Subqueries Embedded in SELECT and FROM - Exercise 1
24.11-SQL Subqueries Embedded in SELECT and FROM - Exercise 2
24.12-SQL Subqueries Nested in SELECT and FROM - Solution 2
24.13-SQL Subqueries Nested in SELECT and FROM - Exercise #1
25.1-Defining Stored Routines
25.2-Defining Stored Routines
25.3-Create Stored Procedures with MySQL Syntax
25.4-An Example of Stored Procedures Part I
25.5-An Example of Stored Procedures Part II
25.6-An Example of Stored Procedures Part II - Exercise
25.7-An Example of Stored Procedures Part II - Solution
25.8-Creating a Procedure in MySQL Another Way
25.9-Create Stored Procedures with an Input Parameter
25.10-Create Stored Procedures with an Output Parameter
25.11-Create Stored Procedures with an Output Parameter - Exercise
25.12-Stored Procedures with an Output Parameter - Solution
25.13-SQL Variables
25.14-SQL Variables - Exercise
25.15-SQL Variables - Solution
25.16-The Benefit of User-Defined Functions in MySQL
25.17-Error Code: 1418.
25.18-The Benefit of User-Defined Functions in MySQL - Exercise
25.19-The Benefit of User-Defined Functions in MySQL - Solution
25.20-Concluding Stored Routines
25.21-Concluding Stored Routines
26.1-The SQL CASE Statement
26.2-The SQL CASE Statement - Exercise 1
26.3-THE SQL CASE Statement - Solution 1
26.4-THE SQL CASE Statement - Exercise 2
26.5-THE SQL CASE Statement - Solution 2
26.6-THE SQL CASE Statement - Exercise 3
26.7-THE SQL CASE Statement - Solution 3
26.8-The SQL CASE Statement - Exercise #1
26.9-The SQL CASE Statement - Exercise #2
26.10-The SQL CASE Statement - Exercise #3
27.1-Introduction to MySQL Window Functions
27.2-The ROW_NUMBER() Ranking Window Function and the Relevant MySQL Syntax
27.3-The ROW_NUMBER Ranking Window Function - Exercise
27.4-The ROW_NUMBER Ranking Window Function - Solution
27.5-The ROW_NUMBER() Ranking Window Function - Exercise #1
27.6-The ROW_NUMBER() Ranking Window Function - Exercise #2
27.7-A Note on Using Several Window Functions in a Query
27.8-A Note on Using Several Window Functions in a Query - Exercise
27.9-A Note on Using Several Window Functions in a Query - Solution
27.10-A Note on Using Several Window Functions - Exercise #1
27.11-A Note on Using Several Window Functions - Exercise #2
27.12-MySQL Window Functions Syntax
27.13-MySQL Window Functions Syntax - Exercise
27.14-MySQL Window Functions Syntax - Solution
27.15-MySQL Window Functions Syntax - Exercise #1
27.16-The PARTITION BY Clause vs the GROUP BY Clause
27.17-The PARTITION BY Clause vs the GROUP BY Clause - Exercise
27.18-The PARTITION BY Clause vs the GROUP BY Clause - Solution
27.19-The PARTITION BY Clause vs the GROUP BY Clause - Exercise #1
27.20-The PARTITION BY Clause vs the GROUP BY Clause - Exercise #2
27.21-The PARTITION BY Clause vs the GROUP BY Clause - Exercise #3
27.22-The MySQL RANK() and DENSE_RANK() Window Functions
27.23-The MySQL RANK() and DENSE_RANK() Window Functions - Exercise
27.24-The MySQL RANK() and DENSE_RANK() Window Functions - Solution
27.25-The MySQL RANK() and DENSE_RANK() Window Functions - Exercise #1
27.26-The MySQL RANK() and DENSE_RANK() Window Functions - Exercise #2
27.27-The MySQL RANK() and DENSE_RANK() Window Functions - Exercise #3
27.28-Working with MySQL Ranking Window Functions and Joins Together
27.29-Working with MySQL Ranking Window Functions and Joins Together - Exercise
27.30-Working with MySQL Ranking Window Functions and Joins Together - Solution
27.31-MySQL Ranking Window Functions and JOINs - Exercise #1
27.32-MySQL Ranking Window Functions and JOINs - Exercise #2
27.33-The LAG() and LEAD() Value Window Functions
27.34-The LAG() and LEAD() Value Window Functions - Exercise
27.35-The LAG() and LEAD() Value Window Functions - Solution
27.36-The LAG() and LEAD() Value Window Functions - Exercise #1
27.37-The LAG() and LEAD() Value Window Functions - Exercise #2
27.38-MySQL Aggregate Functions in the Context of Window Functions - Part I
27.39-MySQL Aggregate Functions in the Context of Window Functions - Part I-Exercise
27.40-MySQL Aggregate Functions in the Context of Window Functions - Part I-Solution
27.41-MySQL Aggregate Functions in the Context of Window Functions - Part II
27.42-MySQL Aggregate Functions in the Context of Window Functions - Part II-Exercise
27.43-MySQL Aggregate Functions in the Context of Window Functions - Part II-Solution
27.44-MySQL Aggregate Functions in the Context of Window Functions - Exercise #1
27.45-MySQL Aggregate Functions in the Context of Window Functions - Exercise #2
28.1-MySQL Common Table Expressions - Introduction
28.2-An Alternative Solution to the Same Task
28.3-An Alternative Solution to the Same Task-Exercise
28.4-An Alternative Solution to the Same Task-Solution
28.5-An Alternative Solution to the Same Task - Exercise #1
28.6-An Alternative Solution to the Same Task - Exercise #2
28.7-Using Multiple Subclauses in a WITH Clause - Part I
28.8-Using Multiple Subclauses in a WITH Clause - Part II
28.9-Using Multiple Subclauses in a WITH Clause-Exercise
28.10-Using Multiple Subclauses in a WITH Clause-Solution
28.11-Referring to Common Table Expressions in a WITH Clause
28.12-Using Multiple Subclauses in a WITH Clause - Exercise #1
28.13-Using Multiple Subclauses in a WITH Clause - Exercise #2
28.14-Using Multiple Subclauses in a WITH Clause - Exercise #3
29.1-MySQL Temporary Tables - Introduction
29.2-MySQL Temporary Tables in Action
29.3-MySQL Temporary Tables in Action-Exercise
29.4-MySQL Temporary Tables in Action-Solution
29.5-MySQL Temporary Tables - Exercise #1
29.6-MySQL Temporary Tables - Exercise #2
29.7-Other Features of MySQL Temporary Tables
29.8-Other Features of MySQL Temporary Tables-Exercise
29.9-Other Features of MySQL Temporary Tables-Solution
29.10-MySQL Temporary Tables - Other Features - Exercise #1
29.11-MySQL Temporary Tables - Other Features - Exercise #2
29.12-MySQL Temporary Tables - Other Features - Exercise #3
29.13-MySQL Temporary Tables - Other Features - Exercise #4
30.1-Why Use Tableau: Make Your Data Make an Impact
30.2-Let's Download Tableau Public
30.3-Connecting Data in Tableau
30.4-Exploring Tableau's Interface
30.5-Let's Create our first Chart in Tableau!
31.1-Duplicating a Sheet
31.2-Creating a Table
31.3-Creating Custom Fields
31.4-Creating a Custom Field and Adding Calculations to a Table
31.5-Adding Totals and Subtotals
31.6-Adding a Custom Calculation
31.7-Inserting a Filter
31.8-Working with Joins in Tableau
32.1-Introduction to the Exercise
32.2-Let's Create a Dashboard - Visualizing the Three Charts We Want to Create
32.3-Using Joins in Tableau
32.4-Performing a Numbers Check - Attempt #1
32.5-Blending Data in Tableau
32.6-Performing a Numbers Check - Attempt #2
32.7-First Chart
32.8-Second Chart
32.9-Third Chart
32.10-Creating and Formatting a Dashboard
32.11-Adding Interactive Filters for Improved Analysis
32.12-Interactive Filters - fix
33.1-Introduction to Software Integration
33.2-Combining SQL and Tableau
33.3-Loading the Database
33.4-Loading the Database
34.1-Problem 1: Task
34.2-Problem 1: Task - Text
34.3-Important clarification!
34.4-Problem 1: Solution in SQL
34.5-Problem 1: Solution in SQL - Code
34.6-Exporting Your Output from SQL and Loading it in Tableau
34.7-Chart 1: Visualizing the Solution in Tableau - Part I
34.8-Chart 1: Visualizing the Solution in Tableau - Part II
34.9-MySQL and Tableau - Task/Exercise #1
35.1-Problem 2: Task
35.2-Problem 2: Task - Text
35.3-Problem 2: Solution in SQL
35.4-Problem 2: Solution in SQL - Code
35.5-Chart 2: Visualizing the Solution in Tableau
35.6-MySQL and Tableau - Task/Exercise #2
36.1-Problem 3: Task
36.2-Problem 3: Task - Text
36.3-Problem 3: Solution in SQL
36.4-Problem 3: Solution in SQL - Code
36.5-Chart 3: Visualizing the Solution in Tableau
36.6-MySQL and Tableau - Task/Exercise #3
37.1-Problem 4: Task
37.2-Problem 4: Task - Text
37.3-Problem 4: Solution in SQL
37.4-Problem 4: Solution in SQL - Code
37.5-Chart 4: Visualizing the Solution in Tableau
38.1-Problem 5: Organizing Charts 1-4 into a Beautiful Dashboard
39.1-A 5-minute explanation of Programming
39.2-A 5-minute explanation of Programming
39.3-Why use Python?
39.4-Why Use Python?
39.5-Why use Jupyter?
39.6-Why Use Jupyter?
39.7-How to Install Python and Jupyter
39.8-Understanding Jupyter’s Interface – Dashboard
39.9-Understanding Jupyter’s Interface – Prerequisites for Coding
39.10-Understanding Jupyter's Interface
39.11-Python 2 vs Python 3
40.1-Python Variables
40.2-Python Variables - Exercise #1
40.3-Python Variables - Exercise #2
40.4-Python Variables - Exercise #3
40.5-Python Variables - Exercise #4
40.6-Python Variables
40.7-Understanding Numbers and Boolean Values
40.8-Numbers and Boolean Values - Exercise #1
40.9-Numbers and Boolean Values - Exercise #2
40.10-Numbers and Boolean Values - Exercise #3
40.11-Numbers and Boolean Values - Exercise #4
40.12-Numbers and Boolean Values - Exercise #5
40.13-Understanding Numbers and Boolean Values
40.14-Strings
40.15-Strings - Exercise #1
40.16-Strings - Exercise #2
40.17-Strings - Exercise #3
40.18-Strings - Exercise #4
40.19-Strings - Exercise #5
40.20-Strings
41.1-The Arithmetic Operators of Python
41.2-The Arithmetic Operators in Python - Exercise #1
41.3-The Arithmetic Operators in Python - Exercise #2
41.4-The Arithmetic Operators in Python - Exercise #3
41.5-The Arithmetic Operators in Python - Exercise #4
41.6-The Arithmetic Operators in Python - Exercise #5
41.7-The Arithmetic Operators in Python - Exercise #6
41.8-The Arithmetic Operators in Python - Exercise #7
41.9-The Arithmetic Operators in Python - Exercise #8
41.10-Using Arithmetic Operators in Python
41.11-What is the Double Equality Sign?
41.12-What is the Double Equality Sign? - Exercise #1
41.13-What is the Double Equality Sign?
41.14-How to Reassign Values
41.15-How to Reassign Values - Exercise #1
41.16-How to Reassign Values - Exercise #2
41.17-How to Reassign Values - Exercise #3
41.18-How to Reassign Values - Exercise #4
41.19-How to Reassign Values
41.20-How to Add Comments
41.21-How to Add Comments
41.22-Understanding Line Continuation
41.23-Understanding Line Continuation - Exercise #1
41.24-How to Index Elements
41.25-How to Index Elements - Exercise #1
41.26-How to Index Elements - Exercise #2
41.27-How to Index Elements
41.28-How to Structure Your Code with Indentation
41.29-How to Structure Your Code with Indentation - Exercise #1
41.30-How to Structure Your Code with Indentation
42.1-Python's Comparison Operators
42.2-Python's Comparison Operators - Exercise #1
42.3-Python's Comparison Operators - Exercise #2
42.4-Python's Comparison Operators - Exercise #3
42.5-Python's Comparison Operators - Exercise #4
42.6-Python's Comparison Operators
42.7-Python's Logical and Identity Operators
42.8-Python's Logical and Identity Operators - Exercise #1
42.9-Python's Logical and Identity Operators - Exercise #2
42.10-Python's Logical and Identity Operators - Exercise #3
42.11-Python's Logical and Identity Operators - Exercise #4
42.12-Python's Logical and Identity Operators - Exercise #5
42.13-Python's Logical and Identity Operators - Exercise #6
42.14-Python's Logical and Identity Operators
43.1-Getting to know the IF Statement
43.2-The IF Statement - Exercise #1
43.3-The IF Statement - Exercise #2
43.4-Getting to know the IF Statement
43.5-Adding an ELSE statement
43.6-The ELSE Statement - Exercise #1
43.7-Else if, for Brief – ELIF
43.8-The ELIF Statement - Exercise #1
43.9-The ELIF Statement - Exercise #2
43.10-An Additional Explanation of Boolean Values
43.11-An Additional Explanation of Boolean Values
44.1-How to Define a Function in Python
44.2-How to Create a Function with a Parameter
44.3-How to Create a Function with a Parameter - Exercise #1
44.4-How to Create a Function with a Parameter - Exercise #2
44.5-Define a Function in Another Way
44.6-Define a Function in Another Way - Exercise #1
44.7-How to Use a Function within a Function
44.8-How to Use a Function within a Function - Exercise #1
44.9-Use Conditional Statements and Functions Together
44.10-Conditional Statements and Functions - Exercise #1
44.11-How to Create Functions Which Contain a Few Arguments
44.12-Built-In Functions in Python Worth Knowing
44.13-Built-In Function in Python Worth Knowing - Exercise #1
44.14-Built-In Function in Python Worth Knowing - Exercise #2
44.15-Built-In Function in Python Worth Knowing - Exercise #3
44.16-Built-In Function in Python Worth Knowing - Exercise #4
44.17-Built-In Function in Python Worth Knowing - Exercise #5
44.18-Built-In Function in Python Worth Knowing - Exercise #6
44.19-Built-In Function in Python Worth Knowing - Exercise #7
44.20-Built-In Function in Python Worth Knowing - Exercise #8
44.21-Built-In Function in Python Worth Knowing - Exercise #9
44.22-Python - Functions
45.1-Introduction to Lists
45.2-Introduction to Lists - Exercise #1
45.3-Introduction to Lists - Exercise #2
45.4-Introduction to Lists - Exercise #3
45.5-Introduction to Lists - Exercise #4
45.6-Introduction to Lists - Exercise #5
45.7-Introduction to Lists
45.8-Using Methods in Python
45.9-Using Methods in Python - Exercise #1
45.10-Using Methods in Python - Exercise #2
45.11-Using Methods in Python - Exercise #3
45.12-Using Methods in Python - Exercise #4
45.13-Using Methods in Python
45.14-What is List Slicing?
45.15-What is List Slicing? - Exercise #1
45.16-What is List Slicing? - Exercise #2
45.17-What is List Slicing? - Exercise #3
45.18-What is List Slicing? - Exercise #4
45.19-What is List Slicing? - Exercise #5
45.20-What is List Slicing? - Exercise #6
45.21-What is List Slicing? - Exercise #7
45.22-Working with Tuples
45.23-Working with Tuples - Exercise #1
45.24-Working with Tuples - Exercise #2
45.25-Working with Tuples - Exercise #3
45.26-Working with Tuples - Exercise #4
45.27-Python Dictionaries
45.28-Python Dictionaries - Exercise #1
45.29-Python Dictionaries - Exercise #2
45.30-Python Dictionaries - Exercise #3
45.31-Python Dictionaries - Exercise #4
45.32-Python Dictionaries - Exercise #5
45.33-Python Dictionaries - Exercise #6
45.34-Python Dictionaries
46.1-Using For Loops
46.2-Using For Loops - Exercise #1
46.3-Using For Loops - Exercise #2
46.4-Using For Loops
46.5-Using While Loops and Incrementing
46.6-Using While Loops and Incrementing - Exercise #1
46.7-Use the range() Function to Create Lists
46.8-Use the range() Function to Create Lists - Exercise - #1
46.9-Use the range() Function to Create Lists - Exercise - #2
46.10-Use the range() Function to Create Lists - Exercise - #3
46.11-Use the range() Function to Create Lists
46.12-Combine Conditional Statements and Loops
46.13-Conditional Statements and Loops - Exercise #1
46.14-Conditional Statements and Loops - Exercise #2
46.15-Conditional Statements and Loops - Exercise #3
46.16-All In – Conditional Statements, Functions, and Loops
46.17-All In - Conditional Statements, Functions, and Loops - Exercise #1
46.18-How to Iterate over Dictionaries
46.19-How to Iterate over Dictionaries - Exercise #1
46.20-How to Iterate over Dictionaries - Exercise #2
47.1-Introduction to Object Oriented Programming (OOP)
47.2-Introduction to Object Oriented Programming (OOP)
47.3-Using Modules and Packages
47.4-Using Modules and Packages
47.5-What is the Standard Library?
47.6-What is the Standard Library?
47.7-How to Import Modules in Python
47.8-How to Import Modules in Python
48.1-Getting Started with Data, Servers, Clients, Requests, and Responses
48.2-Getting Started with Data, Servers, Clients, Requests, and Responses
48.3-Getting Started with Data Connectivity, APIs, and Endpoints
48.4-Getting Started with Data Connectivity, APIs, and Endpoints
48.5-Become Better Acquainted with APIs
48.6-Become Better Acquainted with APIs
48.7-Communication through Text Files
48.8-Communication through Text Files
48.9-What is Software Integration and How is it Applied?
48.10-What is Software Integration and How is it Applied?
49.1-Solving a Business Exercise with Python, SQL, and Tableau
49.2-Presenting the Task: Absenteeism at Work
49.3-Presenting the Data Set
49.4-Presenting the Data Set
50.1-How is the Content in the Next Sections Organized?
50.2-How to Import the Data Set in Python
50.3-Exploring the Data Set
50.4-Programming vs the Rest of the World
50.5-A Brief Summary of Regression Analysis
50.6-The Approach we will Take to Solve this Exercise
50.7-Dropping Variables We Don't Need
50.8-EXERCISE - Dropping Variables We Don't Need
50.9-SOLUTION - Dropping Variables We Don't Need
50.10-A Deeper Look at the 'Reasons for Absence' Column
50.11-Splitting a Variable into Multiple Dummy Variables
50.12-EXERCISE - Splitting a Variable into Multiple Dummy Variables
50.13-SOLUTION - Splitting a Variable into Multiple Dummy Variables
50.14-How to Drop a Dummy Variable from the Data Set
50.15-A Statistical Perspective on Dummy Variables
50.16-Categorizing the Various Reasons for Absence
50.17-Concatenation in Python
50.18-EXERCISE - Concatenation in Python
50.19-SOLUTION - Concatenation in Python
50.20-How to Reorder Columns in a DataFrame in Python
50.21-EXERCISE - How to Reorder Columns in a DataFrame in Python
50.22-SOLUTION - How to Reorder Columns in a DataFrame in Python
50.23-Using Checkpoints to Ease Your Work in Jupyter
50.24-EXERCISE - Using Checkpoints to Ease Your Work in Jupyter
50.25-SOLUTION - Using Checkpoints to Ease Your Work in Jupyter
50.26-Analyzing the "Date" Column
50.27-Retrieving the Month Value From the "Date" Column
50.28-Adding the "Day of the Week" Column
50.29-EXERCISE - Dropping Columns
50.30-Analysis of the Next 5 Columns in DF
50.31-Dealing with More Numerical Features which may Behave like Categorical Ones
50.32-A Final Note on this Section
51.1-How to Use the 'absenteeism_module' in Python - Part I
51.2-How to Use the 'absenteeism_module' in Python - Part II
51.3-Creating the 'predicted_outputs' Database in MySQL
51.4-Importing 'pymysql' in Python
51.5-Creating a Connection and Cursor
51.6-EXERCISE - Creating 'df_new_obs'
51.7-Creating the 'predicted_outputs' Table in MySQL
51.8-Executing and SQL SELECT Statement from Python
51.9-Sending Data from Jupyter to Workbench - Part I
51.10-Sending Data from Jupyter to Workbench - Part II
51.11-Sending Data from Jupyter to Workbench - Part III
52.1-EXERCISE - Age vs Probability
52.2-Using Tableau to Analyze Age vs Probability
52.3-EXERCISE - Reasons vs Probability
52.4-Using Tableau to Analyze Reasons vs Probability
52.5-EXERCISE - Transportation Expense vs Probability
52.6-Using Tableau to Analyze Transportation Expense vs Probability
52.7-Completing 100%
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