The Business Intelligence Analyst Course 2024
- Offered byUDEMY
The Business Intelligence Analyst Course 2024 at UDEMY Overview
Duration | 23 hours |
Total fee | ₹599 |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website |
Credential | Certificate |
The Business Intelligence Analyst Course 2024 at UDEMY Highlights
- Earn a Cerificate on successful completion
- Get Full Lifetime Access
- Compatible on Mobile and TV
The Business Intelligence Analyst Course 2024 at UDEMY Course details
- 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
- 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
The Business Intelligence Analyst Course 2024 is a specialized program designed to equip participants with the skills and knowledge essential for a successful career in business intelligence (BI) analysis.
This course covers a comprehensive range of topics essential for understanding and leveraging data to drive strategic business decisions.
Throughout the course, participants will explore advanced techniques for data analysis and interpretation.
This includes using BI tools and platforms to create interactive dashboards and reports that provide valuable insights to stakeholders.
Emphasis is placed on understanding key performance indicators (KPIs), conducting trend analysis, and forecasting based on historical data.
The Business Intelligence Analyst Course 2024 at UDEMY Curriculum
Part 1: Introduction
What Does the Course CoverIntro to Data and Data Science - The Different Data Science Fields
Why Are There So Many Business and Data Science Buzzwords?
Analysis vs Analytics
Intro to Business Analytics, Data Analytics, and Data Science
Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture
An Overview of our Data Science Infographic
Intro to Data and Data Science - The Relationship between Different Fields
When are Traditional data, Big Data, BI, Traditional Data Science and ML applied
Intro to Data and Data Science - What is the Purpose of each Data Science Field
Why do we Need each of these Disciplines?
Intro to Data and Data Science - Common Data Science Techniques
Traditional Data: Techniques
Traditional Data: Real-life Examples
Big Data: Techniques
Big Data: Real-life Examples
Business Intelligence (BI): Techniques
Business Intelligence (BI): Real-life Examples
Traditional Methods: Techniques
Traditional Methods: Real-life Examples
Machine Learning (ML): Techniques
Machine Learning (ML): Types of Machine Learning
Machine Learning (ML): Real-life Examples
Intro to Data and Data Science - Common Data Science Tools
Programming Languages & Software Employed in Data Science - All the Tools Needed
Intro to Data and Data Science - Data Science Career Paths
Data Science Job Positions: What do they Involve and What to Look out for?
Intro to Data and Data Science - Dispelling Common Misconceptions
Dispelling common Misconceptions
Part 2: Statistics - Population and Sample
Population vs sample
Statistics - Descriptive Statistics
Types of Data
Levels of Measurement
Categorical Variables - Visualization Techniques
Categorical Variables Exercise
Numerical Variables - Frequency Distribution Table
Numerical Variables Exercise
The Histogram
Histogram Exercise
Cross Table and Scatter Plot
Cross Tables and Scatter Plots Exercise
Mean, median and mode
Mean, Median and Mode Exercise
Skewness
Skewness Exercise
Variance
Variance Exercise
Standard Deviation and Coefficient of Variation
Standard Deviation and Coefficient of Variation Exercise
Covariance
Covariance Exercise
Correlation Coefficient
Correlation Coefficient Exercise
Statistics - Practical Example: Descriptive Statistics
Practical Example
Practical Example Exercise
Statistics - Inferential Statistics Fundamentals
Introduction
What is a Distribution
The Normal Distribution
The Standard Normal Distribution
The Standard Normal Distribution Exercise
Central Limit Theorem
Standard error
Estimators and Estimates
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
Confidence Intervals; Population Variance Unknown; t-score
Confidence Intervals; Population Variance Unknown; t-score Exercise
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)
Statistics - Practical Example: Inferential Statistics
Practical Example: Inferential Statistics
Practical Example: Inferential Statistics Exercise
Statistics - Hypothesis Testing
The Null vs Alternative Hypothesis
Further Reading on Null and Alternative Hypothesis
Rejection Region and Significance Level
Type I Error and Type II Error
Test for the Mean. Population Variance Known
Test for the Mean. Population Variance Known Exercise
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)
Statistics - Practical Example: Hypothesis Testing
Practical Example: Hypothesis Testing
Practical Example: Hypothesis Testing Exercise
Part 3: Relational Database Theory & Introduction to SQL
Why use SQL?
Why use MySQL?
Introducing Databases
Relational Database Fundamentals
Comparing Databases and Spreadsheets
Important Database Terminology
The Concept of Relational Schemas: Primary Key
The Concept of Relational Schemas: Foreign Key
The Concept of Relational Schemas: Unique Key and Null Values
The Concept of Relational Schemas: Relationships Between Tables
SQL - Install and get to know MySQL
Installing MySQL Workbench and Server
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 - Best SQL Practices
Coding Tips and Best Practices - I
Coding Tips and Best Practices - II
SQL - Loading the 'employees' Database
Loading the 'employees' Database
Loading the 'employees' Database
SQL - Practical Application of the SQL SELECT Statement
Using SELECT - FROM
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 - IS
Using IS NOT - IS - Exercise
Using IS NOT - IS - 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()
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?
What are JOINs? - Exercise 1
What are JOINs? - Exercise 2
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
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
SQL - The CASE Statement
The SQL CASE Statement
The SQL CASE Statement - Exercise 1
THE SQL CASE Statement - Solution 1
THE SQL CASE Statement - Exercise 2
THE SQL CASE Statement - Solution 2
THE SQL CASE Statement - Exercise 3
THE SQL CASE Statement - Solution 3
Part 4: Introduction to Tableau
Why Use Tableau: Make Your Data Make an Impact
Let's Download Tableau Public
Connecting Data in Tableau
Exploring Tableau's Interface
Let's Create our first Chart in Tableau!
Tableau - Tableau functionalities
Duplicating a Sheet
Creating a Table
Creating Custom Fields
Creating a Custom Field and Adding Calculations to a Table
Adding Totals and Subtotals
Adding a Custom Calculation
Inserting a Filter
Working with Joins in Tableau
Tableau - The Tableau Exercise
Introduction to the 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
Part 5: Combining SQL and Tableau - Introduction
Introduction to Software Integration
Combining SQL and Tableau
Loading the Database
Loading the Database
Combining SQL and Tableau - Problem 1
Problem 1: Task
Problem 1: Task - Text
Important clarification!
Problem 1: Solution in SQL
Problem 1: Solution in SQL - Code
Exporting Your Output from SQL and Loading it in Tableau
Chart 1: Visualizing the Solution in Tableau - Part I
Chart 1: Visualizing the Solution in Tableau - Part II
Combining SQL and Tableau - Problem 2
Problem 2: Task
Problem 2: Task - Text
Problem 2: Solution in SQL
Problem 2: Solution in SQL - Code
Chart 2: Visualizing the Solution in Tableau
Combining SQL and Tableau - Problem 3
Problem 3: Task
Problem 3: Task - Text
Problem 3: Solution in SQL
Problem 3: Solution in SQL - Code
Chart 3: Visualizing the Solution in Tableau
Combining SQL and Tableau - Problem 4
Problem 4: Task
Problem 4: Task - Text
Problem 4: Solution in SQL
Problem 4: Solution in SQL - Code
Chart 4: Visualizing the Solution in Tableau
Combining SQL and Tableau - Problem 5
Problem 5: Organizing Charts 1-4 into a Beautiful Dashboard
Part 6: Introduction to Programming with Python
A 5-minute explanation of Programming
Why use Python?
Why use Jupyter?
How to Install Python and Jupyter
Understanding Jupyter?????????????????s Interface ????????????????? Dashboard
Understanding Jupyter?????????????????s Interface ????????????????? Prerequisites for Coding
Python 2 vs Python 3
Python - Python Variables and Data Types
Python Variables
Understanding Numbers and Boolean Values
Strings
Python - Python Syntax Fundamentals
The Arithmetic Operators of Python
What is the Double Equality Sign?
How to Reassign Values
How to Add Comments
Understanding Line Continuation
How to Index Elements
How to Structure Your Code with Indentation
Python - Other Python Operators
Python's Comparison Operators
Python's Logical and Identity Operators
Python - Conditional Statements
Getting to know the IF Statement
Adding an ELSE statement
Else if, for Brief ????????????????? ELIF
An Additional Explanation of Boolean Values
Python - Functions
How to Define a Function in Python
How to Create a Function with a Parameter
Define a Function in Another Way
How to use a Function within a Function
Use Conditional Statements and Functions Together
How to Create Functions Which Contain a Few Arguments
Built-In Functions in Python Worth Knowing
Python - Python Sequences
Introduction to Lists
Using Methods in Python
What is List Slicing?
Working with Tuples
Python Dictionaries
Python - Using Iterations
Using For Loops
Using While Loops and Incrementing
Use the range() Function to Create Lists
Combine Conditional Statements and Loops
All In ????????????????? Conditional Statements, Functions, and Loops
How to Iterate over Dictionaries
Python - Advanced Python tools
Introduction to Object Oriented Programming (OOP)
Using Modules and Packages
What is the Standard Library?
How to Import Modules in Python
Part 7: Integration - Software Integration
Getting Started with Data, Servers, Clients, Requests, and Responses
Getting Started with Data Connectivity, APIs, and Endpoints
Become Better Acquainted with APIs
Communication through Text Files
What is Software Integration and How is it Applied?
Integration - What is contained in this Course?
Solving a Business Exercise with Python, SQL, and Tableau
Presenting the Task: Absenteeism at Work
Presenting the Data Set
Integration - Data Preprocessing Step by Step
How is the Content in the Next Sections Organized?
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
EXERCISE - 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
Integration - Integrating Python and SQL
How to Use the 'absenteeism_module' in Python - Part I
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
EXERCISE - Age vs Probability
Using Tableau to Analyze Age vs Probability
EXERCISE - Reasons vs Probability
Using Tableau to Analyze Reasons vs Probability
EXERCISE - Transportation Expense vs Probability
Using Tableau to Analyze Transportation Expense vs Probability