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The Business Intelligence Analyst Course 2023

The skills you need to become a BI Analyst - Statistics, Database theory, SQL, Tableau – Everything is included
Instructor:
365 Careers
224,252 students enrolled
English [CC] More
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

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:   

  • Pre-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 subscribe today. The only regret you will have is that you didn’t find this course sooner!

Part 1: Introduction

1
What Does the Course Cover
2
Download All Resources

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

1
Why Are There So Many Business and Data Science Buzzwords?
2
Analysis vs Analytics
3
Intro to Business Analytics, Data Analytics, and Data Science
4
Intro to Business Analytics, Data Analytics, and Data Science
5
Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture
6
Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture
7
An Overview of our Data Science Infographic
8
An Overview of our Data Science Infographic

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

1
When are Traditional data, Big Data, BI, Traditional Data Science and ML applied
2
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

1
Why do we Need each of these Disciplines?
2
Why do we Need each of these Disciplines?

Intro to Data and Data Science - Common Data Science Techniques

1
Traditional Data: Techniques
2
Traditional Data: Techniques
3
Traditional Data: Real-life Examples
4
Big Data: Techniques
5
Big Data: Techniques
6
Big Data: Real-life Examples
7
Business Intelligence (BI): Techniques
8
Business Intelligence (BI): Techniques
9
Business Intelligence (BI): Real-life Examples
10
Traditional Methods: Techniques
11
Traditional Methods: Techniques
12
Traditional Methods: Real-life Examples
13
Machine Learning (ML): Techniques
14
Machine Learning (ML): Techniques
15
Machine Learning (ML): Types of Machine Learning
16
Machine Learning (ML): Types of Machine Learning
17
Machine Learning (ML): Real-life Examples
18
Machine Learning (ML): Real-life Examples

Intro to Data and Data Science - Common Data Science Tools

1
Programming Languages & Software Employed in Data Science - All the Tools Needed
2
Programming Languages & Software Employed in Data Science - All the Tools Needed

Intro to Data and Data Science - Data Science Career Paths

1
Data Science Job Positions: What do they Involve and What to Look out for?
2
Data Science Job Positions: What do they Involve and What to Look out for?

Intro to Data and Data Science - Dispelling Common Misconceptions

1
Dispelling common Misconceptions
2
Dispelling common Misconceptions

Part 2: Statistics - Population and Sample

1
Population vs sample
2
Population and Sample

Statistics - Descriptive Statistics

1
Types of Data
2
Types of data
3
Levels of Measurement
4
Levels of measurement
5
Categorical Variables - Visualization Techniques
6
Categorical variables. Visualization Techniques
7
Categorical Variables Exercise
8
Numerical Variables - Frequency Distribution Table
9
Numerical variables. Using a frequency distribution table
10
Numerical Variables Exercise
11
The Histogram
12
The Histogram
13
Histogram Exercise
14
Cross Table and Scatter Plot
15
Cross Tables and Scatter Plots
16
Cross Tables and Scatter Plots Exercise
17
Mean, median and mode
18
Mean, Median and Mode Exercise
19
Skewness
20
Skewness
21
Skewness Exercise
22
Variance
23
Variance Exercise
24
Standard Deviation and Coefficient of Variation
25
Standard deviation
26
Standard Deviation and Coefficient of Variation Exercise
27
Covariance
28
Covariance
29
Covariance Exercise
30
Correlation Coefficient
31
Correlation Coefficient
32
Correlation Coefficient Exercise

Statistics - Practical Example: Descriptive Statistics

1
Practical Example
2
Practical Example Exercise

Statistics - Inferential Statistics Fundamentals

1
Introduction
2
What is a Distribution
3
What is a Distribution
4
The Normal Distribution
5
The Normal Distribution
6
The Standard Normal Distribution
7
The Standard Normal Distribution
8
The Standard Normal Distribution Exercise
9
Central Limit Theorem
10
Central Limit Theorem
11
Standard error
12
Standard error
13
Estimators and Estimates
14
Estimators and Estimates
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Includes

22 hours on-demand video
177 articles
Certificate of Completion
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