3 modules + 1 final project
German or English
Certificate of completion
Chapter 1: Relational Databases
The first chapter introduces you to the topic of databases. You will learn what databases are, where they are used and why. You will understand how relational databases are constructed and familiarize yourself with their advantages and disadvantages. You will delve deeper into ER diagrams(Entity Relationship Model) and learn how to read them. You will build your knowledge around the most important SQL terms and locate SQL as the language to communicate with relational databases. You will get an overview of how this interaction works and what SQL can do.
Chapter 2: Basic SQL
In the second chapter, you will learn how to write SQL queries and read relational databases in order to extract company-relevant information. You will distinguish between data formats and learn about Boolean logic and filter tables with Boolean operators. In the first practical project, you will apply the previous learning content and build a toolkit to filter, group, sort and join data.
Chapter 3: Advanced SQL
In the third chapter, you will focus on advanced SQL concepts and techniques and how to use them to overcome the limitations of basic SQL queries. This includes 4 concepts for reusing query results: subqueries, views, Common Table Expressions (CTEs) and table creation. In multiple use cases, you will learn advanced filtering and joining methods using nested SQL queries. In addition, you will learn how to accelerate your queries (indexes) and apply all the learning content taught so far in the second practical project.
Chapter 4: Analytical Functions and Excercise Project
The final chapter focuses on the practical project. You will analyze a completely new database independently – from the first exploration to the last query. For this, we teach you two more important concepts that often come up in everyday work with SQL: you will learn how to optimally use arithmetic with SQL and how to calculate with SELECT. You also build up in-depth knowledge of analytical functions in order to create ranking lists or calculate running totals over longer periods of time. To do so, you determine statistical parameters such as correlations, standard deviations and medians, create window functions and learn to control various SQL dialects.
Chapter 1: Introduction to Power BI
In the first chapter, you will learn why data-driven decisions are important and what the workflow of data analyses looks like. You will learn about the most important basic functions of Microsoft Power BI – including data, model, and report views as well as the filter functions. You will load multiple data sets in the Data View to create a data model and your first report.
Chapter 2: Data Preparation and Visualization
In the second chapter, you will learn about data visualization best practices and how to modify and format visualizations using hands-on exercises. Power BI offers numerous visualizations that you can use in reports and dashboards. You will learn how to avoid typical mistakes and get guidelines on how to format graphics in an understandable way. You will then learn how to use the Power Query Editor with Power BI Desktop to process data and link disparate data sources.
Chapter 3: Dashboards and Data Storytelling
In the third chapter, you will learn how to arrange your reports and analyses in dashboards and how to communicate them to relevant target groups in an efficient, easy-to-understand way using the most important principles of data storytelling. You will also learn advanced BI skills. You will learn the basics of Data Analysis Expressions (DAX language). You will learn basic concepts and best practices for incorporating DAX into your reports and learn to write complex DAX code for calculations to generate columns, metrics, and tables.
Chapter 4: Advanced Topics
The fourth chapter focuses on basic concepts of statistics. We will provide you with the best practices for valid statistical data analysis. Finally, you will explore advanced business intelligence methods based on statistics and machine learning. At the end, you will be able to use a cross-page drilldown and perform an influence factor analysis with the help of the drillthrough.
In the final project, you will apply your previous learning and go through the entire process of data analysis – from importing and cleansing data to analysis and data storytelling. You will deepen your newly-acquired BI skills by analyzing air traffic tardiness at a major hub using real data sets. You will use SQL and MS Power BI together and investigate and visualize flight delays at the Los Angeles International Airport, preparing a results’ presentation.
Yes, our online training courses should offer you the greatest possible flexibility. Basically, we recommend planning six to eight hours a week for studying. When you want to schedule this time is up to you and is not prescribed by us. In our career paths, the Data Analyst and Data Scientist course, we offer you live webinars where you can ask our mentors questions, but you don’t have to attend if it doesn’t fit into your schedule.
(Participants in our funded training courses are an exception. They have to attend a fixed number of hours per week and are obliged to take part in the live webinars.)