6 Essential Skills to Make A Great BI Analyst Series 2

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Online

£ 10 + VAT

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    Course

  • Methodology

    Online

  • Start date

    Different dates available

About this courseHi! Welcome to our Business Intelligence Analyst Course Series. This course entails the six essential skills you need to make a great BI analystWe are excited to present you a course series that stands out.This BI program is different than the rest of the materials available online. 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! Introduction to Data and Data Science 
Statistics and Excel 
Database theory 
SQL 
Tableau 
SQL + Tableau 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...

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this 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 

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

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This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Visualisation
  • MS Excel
  • Business Intelligence
  • Statistics
  • Database training
  • SQL
  • Database
  • Excel

Course programme

Descriptive Statistics 19 lectures 49:44 Lesson 1: Understanding Population and Sample Data Lesson 2: Types of Data and Levels of Measurement Lesson 3: Visualisation Techniques for Categorical and Numerical Variables Lesson 4: Calculating Measures of Central Tendency Lesson 5: Calculating Measures of Asymmetry Lesson 6: How to Quantify Variability Lesson 7 Standard Deviation and Coefficient of Variation Lesson 8: Measuring Relationships Between two Variables Lesson 9: Correlation Coefficient Population vs Sample Types of Data and Levels of Measurement Resources Exercise 1 Resource Exercise 1b Resources Exercise 2a Resources Exercise 2b Resources Exercise 3 Resource Exercise 3b Resource Exercise 4 Resource Exercise 5 Resource Exercise 6 Resource Exercise 7 Descriptive Statistics 19 lectures 49:44 Lesson 1: Understanding Population and Sample Data Lesson 2: Types of Data and Levels of Measurement Lesson 3: Visualisation Techniques for Categorical and Numerical Variables Lesson 4: Calculating Measures of Central Tendency Lesson 5: Calculating Measures of Asymmetry Lesson 6: How to Quantify Variability Lesson 7 Standard Deviation and Coefficient of Variation Lesson 8: Measuring Relationships Between two Variables Lesson 9: Correlation Coefficient Population vs Sample Types of Data and Levels of Measurement Resources Exercise 1 Resource Exercise 1b Resources Exercise 2a Resources Exercise 2b Resources Exercise 3 Resource Exercise 3b Resource Exercise 4 Resource Exercise 5 Resource Exercise 6 Resource Exercise 7 Lesson 1: Understanding Population and Sample Data Lesson 1: Understanding Population and Sample Data Lesson 1: Understanding Population and Sample Data Lesson 1: Understanding Population and Sample Data Lesson 2: Types of Data and Levels of Measurement Lesson 2: Types of Data and Levels of Measurement Lesson 2: Types of Data and Levels of Measurement Lesson 2: Types of Data and Levels of Measurement Lesson 3: Visualisation Techniques for Categorical and Numerical Variables Lesson 3: Visualisation Techniques for Categorical and Numerical Variables Lesson 3: Visualisation Techniques for Categorical and Numerical Variables Lesson 3: Visualisation Techniques for Categorical and Numerical Variables Lesson 4: Calculating Measures of Central Tendency Lesson 4: Calculating Measures of Central Tendency Lesson 4: Calculating Measures of Central Tendency Lesson 4: Calculating Measures of Central Tendency Lesson 5: Calculating Measures of Asymmetry Lesson 5: Calculating Measures of Asymmetry Lesson 5: Calculating Measures of Asymmetry Lesson 5: Calculating Measures of Asymmetry Lesson 6: How to Quantify Variability Lesson 6: How to Quantify Variability Lesson 6: How to Quantify Variability Lesson 6: How to Quantify Variability Lesson 7 Standard Deviation and Coefficient of Variation Lesson 7 Standard Deviation and Coefficient of Variation Lesson 7 Standard Deviation and Coefficient of Variation Lesson 7 Standard Deviation and Coefficient of Variation Lesson 8: Measuring Relationships Between two Variables Lesson 8: Measuring Relationships Between two Variables Lesson 8: Measuring Relationships Between two Variables Lesson 8: Measuring Relationships Between two Variables Lesson 9: Correlation Coefficient Lesson 9: Correlation Coefficient Lesson 9: Correlation Coefficient Lesson 9: Correlation Coefficient Population vs Sample Population vs Sample Population vs Sample Population vs Sample Types of Data and Levels of Measurement Types of Data and Levels of Measurement Types of Data and Levels of Measurement Types of Data and Levels of Measurement Resources Exercise 1 Resources Exercise 1 Resources Exercise 1 Resources Exercise 1 Resource Exercise 1b Resource Exercise 1b Resource Exercise 1b Resource Exercise 1b Resources Exercise 2a Resources Exercise 2a Resources Exercise 2a Resources Exercise 2a Resources Exercise 2b Resources Exercise 2b Resources Exercise 2b Resources Exercise 2b Resources Exercise 3 Resources Exercise 3 Resources Exercise 3 Resources Exercise 3 Resource Exercise 3b Resource Exercise 3b Resource Exercise 3b Resource Exercise 3b Resource Exercise 4 Resource Exercise 4 Resource Exercise 4 Resource Exercise 4 Resource Exercise 5 Resource Exercise 5 Resource Exercise 5 Resource Exercise 5 Resource Exercise 6 Resource Exercise 6 Resource Exercise 6 Resource Exercise 6 Resource Exercise 7 Resource Exercise 7 Resource Exercise 7 Resource Exercise 7 Inferential Statistics 13 lectures 44:01 Lesson 1: Distribution Lesson 2: Normal Distribution Lesson 3: Standard Normal Distribution Lesson 4: Central Limit Theorem Lesson 4b: Standard Error Lesson 5: Estimator and Estimates Lesson 6: Confidence Interval Lesson 7: Confidence Intervals Clarification with Student's T Distribution Lesson 8: Population Variance Unknown Resource Exercise 1 Resource Exercise 2 Resource Exercise 3 Resource Exercise Inferential Statistics trong Resource Exercise C Resource Exercise C Resource Exercise D Resource Exercise D Resource Exercise D Resource Exercise D

Additional information

No prior experience is required. We will start from the very basics You’ll need to install MySQL, Tableau Public, and Anaconda. We will show you how to do it step by step Microsoft Excel 2003, 2010, 2013, 2016, or 365

6 Essential Skills to Make A Great BI Analyst Series 2

£ 10 + VAT