4.52 (27944 reviews)

$94.99

Regular PriceWhat you will 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

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 dashboardsLearning 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!**

Screenshots

Content

Part 1: Introduction

What Does the Course Cover

Intro 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

Intro to Business Analytics, Data Analytics, and Data Science

Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture

Adding Business Intelligence (BI), Machine Learning (ML), and AI to the Picture

An Overview of our Data Science Infographic

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

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?

Why do we Need each of these Disciplines?

Intro to Data and Data Science - Common Data Science Techniques

Traditional Data: 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

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

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?

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

Dispelling common Misconceptions

Part 2: Statistics - Population and Sample

Population vs sample

Population and Sample

Statistics - Descriptive Statistics

Types of Data

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

Statistics - Practical Example: Descriptive Statistics

Practical Example

Practical Example Exercise

Statistics - Inferential Statistics Fundamentals

Introduction

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

Statistics - Inferential Statistics: Confidence Intervals

What are 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)

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

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)

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 SQL?

Why use MySQL?

Why use MySQL?

Introducing Databases

Introducing Databases

Relational Database Fundamentals

Relational Database Fundamentals

Comparing Databases and Spreadsheets

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 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 - I

Coding Tips and Best Practices - II

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 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()

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

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

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

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

Python Variables

Understanding Numbers and Boolean Values

Understanding Numbers and Boolean Values

Strings

Strings

Python - Python Syntax Fundamentals

The Arithmetic Operators of Python

Using Arithmetic Operators in Python

What is the Double Equality Sign?

What is the Double Equality Sign?

How to Reassign Values

How to Reassign Values

How to Add Comments

How to Add Comments

Understanding Line Continuation

How to Index Elements

How to Index Elements

How to Structure Your Code with Indentation

How to Structure Your Code with Indentation

Python - Other Python Operators

Python's Comparison Operators

Python's Comparison Operators

Python's Logical and Identity Operators

Python's Logical and Identity Operators

Python - Conditional Statements

Getting to know the IF Statement

Getting to know the IF Statement

Adding an ELSE statement

Else if, for Brief – ELIF

An Additional Explanation of Boolean Values

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 - Functions

Python - Python Sequences

Introduction to Lists

Introduction to Lists

Using Methods in Python

Using Methods in Python

What is List Slicing?

Working with Tuples

Python Dictionaries

Python Dictionaries

Python - Using Iterations

Using For Loops

For Loops

Using While Loops and Incrementing

Use the range() Function to Create Lists

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)

Introduction to Object Oriented Programming (OOP)

Using Modules and Packages

Using Modules and Packages

What is the Standard Library?

What is the Standard Library?

How to Import Modules in Python

How to Import Modules in Python

Part 7: Integration - Software Integration

Getting Started with Data, Servers, Clients, Requests, and Responses

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?

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

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

Reviews

J

Johnnatan9 October 2020

1. The statistics that they teach at the beginning, they do not use it in practical exercises. 2. They talk about Panda's topics, where they should have a Panda module since the topics they talk about are spoken very superficially. 3. In the Python and SQL exercise, we have to downgrade the Anaconda version, otherwise the exercise doesn't work.

S

Saket8 October 2020

Honestly this is not what I expected from the course. A short introduction to the termnologies would have done the work rather than breifing them up and making them so complex and difficult to understand. Also what I expected was to how to do these analysis or analytics.

B

Burak7 October 2020

Issues mentioned are quite related to my profession. This course gives me a different perspective to look at those issues.

G

Gheorghe6 October 2020

I took this course just to have an idea about what all this is about. A few months later, I decided to go to college for a similar program. The way this course is taught is fantastic. If compared to how it is done in college, it's like the distance between the moon and the sun. Very comprehensive and well presented with lots of information delivered in a very fun and friendly environment. A massive THANK YOU to the awesome team that got this done. Great efforts. Keep it going.

M

Michael1 October 2020

Awesome course anyone looking to become a BI analyst should take, great content, examples and explanations

D

Divyanshu27 February 2020

A good portion of this course is very theoritical and very very basic. There is probably a way to optimize the detailed theoretical explanations on a lot of topics.

S

Santos26 February 2020

Its good the way you introduce to the student to Business Intelligence world clarifying basics terms.

S

Stephen26 February 2020

So far, it is above what I expected. Simplified and well detailed explanations. Makes the course to seem easy

K

Karina25 February 2020

I like the way they explain every topic. Following this course is the best way to know aboy business intelligence

O

Oluwasegun24 February 2020

I have been able to understand the various domains of Business Intelligence as it relates to Data and the Business itself as well as the various boundaries of all the concepts involved.

Y

Yoon23 February 2020

Great categorization of different techniques and ample examples to illustrate where each technique is used. What I learned from this don't only apply to what I want to do day to day later but will certainly help me answer some trick interview questions well

J

Jesse23 February 2020

Great source of information so far. The intros really help to demystify the very confusing terminology in the data science and business analytics world.

M

Michal20 February 2020

It was a good refresher for my Statistics, Python and SQL knowledge and a very good basic background in Tableau as well. I am happy I took this course!

T

Tembela20 February 2020

Yes, as an applications development coordinator, responsible for application, the conversation starts with data first before propose an application to be used. The course is business focus and oriented and assisting

M

Marco19 February 2020

An amazing and comprehensive course. All the contents are delivered in an engaging manner. The explanations are clear and always accompanied by examples that help to illustrate the concepts. Highly recommended.

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