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Introduction to BI and Data Analytics

Further training for lateral entry into the job as a business intelligence analyst or data analyst

Certificate of completion
(Cross) boarding
Full time/part time
German, English
Free of charge with education voucher
Course description

The goal of the introductory course is to provide you with essential prior knowledge and skills that you need for a BI Analyst or Data Analyst advanced training. You will learn to describe the fields of business intelligence and data analytics and to create simple scripts in the Python programming language.

In this training you will learn
Introduction to Data Analytics
Data Analytics Tools
Introduction to Python
  • Introduction to data analysis
    • From collecting the data to visualizing the analysis results
    • Areas of activity Business Intelligence and Data Analytics
  • Basics of the Python programming language
    •  Standard data types
    • Variables
    • Error messages
    • If-Then Branches

Target group

The advanced training is suitable for you and your career aspirations if you have a degree, ideally in the fields of mathematics, computer science, natural sciences, technology, business administration, (business) information technology or have a comparable qualification or previous experience.

Requirements for participation

Basic knowledge of mathematics & statistics

Modules

1
Day 1: Introduction to the learning environment
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Objectives:

  • Description of activities and differences in the areas of business intelligence and data analytics

 

Contents:

  • Welcome round
  • Training procedure and insight into the building blocks
  • Introduction to the learning environment
  • Definitions of the terms "data analysis" and "business intelligence
  • Activities of a BI Analyst
  • Case Study Data Analysis
  • Question to the data
    • Collect data
    • Structure data
    • Data Analysis
    • Visualization of the results

2
Day 2: Activities of a Data Analyst, Introduction to Python Part 1
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Objectives:

  • Situation-appropriate use of the standard data types of the Python programming language and their native methods
  • Use of flow control concepts

 

Contents:

  • Definition of the term "Big Data
  • Activities of a Data Analyst
  • Overview and differentiation of different tools in Business Intelligence and Data Analytics
    • SQL, Power BI, Tableau, Qlik, Python, R and more
  • Introduction to Python Part 1
    • Numbers and in Python
    • Variables
    • Read and understand error messages
    • Text in Python

3
Day 3: Introduction to Python Part 2
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Objectives:

  • Situation-appropriate use of the standard data types of the Python programming language and their native methods
  • Use of flow control concepts

 

Contents:

  • Using functions in Python
  • Boolean data type
  • If-Then Conditions
  • The if statement

4
Day 4: Introduction to Python Part 2
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Objectives:

  • Situation-appropriate use of the standard data types of the Python programming language and their native methods

 

Contents:

  • Repetition of basic data types in Python
  • Lists and loops part 1
    • Create lists
    • Read out lists
    • Change lists
    • List methods
    • Lists in lists

5
Day 5: Introduction to Python Part 2
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Objectives:

  • Use of flow control concepts

 

Contents:

  • The for loop
  • The range function
  • Combine loops and conditions
FAQ
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The StackFuel Data Lab offers me real added value. Here you can feel the practical relevance particularly well. The tasks were always clearly described and presented. So I always knew what I had to do. The training itself was a great experience!
Alexander Gross
Data Analyst at AIC Portaltechnik
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The greatest added value for me is the practical relevance. Thanks to StackFuel, I can quickly implement what I've learned and adapt it for myself. That is the real learning success behind the online trainings.
Lutz Schneider
Strategic IT Buyer at Axel Springer SE
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The content of StackFuel's online training was very practical. There were many good examples and projects. I found that very interesting and instructive. Since the training, my everyday professional life has changed significantly: I am now a data analytics specialist in my department.
Jaroslaw Wojciech Sulak
Specialist for data analysis at IAV GmbH
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The user-friendly and flexible Python programming training has completely changed my view of complex data structures. Thanks to the sustainable and well thought-out learning concept as well as the seamless application of the learning content in the development environment, I can now implement the newly learned knowledge in my everyday job in test automation in greater depth and process data more easily and efficiently since then.
Jenny Lindenau
Technical Manager Test Management at Bank Deutsches Kraftfahrzeuggewerbe GmbH
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