Marcel Mittelstädt

DHBW, Rotebühlplatz 41 · 70178 Stuttgart · contact@marcel-mittelstaedt.com

Lecturing in the fields of Big Data, data engineering, data science, development and architecture of data-intensive applications.

"We must look for the opportunity in every difficulty, instead of being paralyzed at the thought of the difficulty in every opportunity."
- Walter E. Cole





Lecture(-s):

Big Data

Winter Semester 2024/2025

This lecture will give you a brief introduction to so what is called ’Big Data’. We will quickly refresh the basics about databases, data models and data processing you have learned so far and compare those to the distributed world of Big Data. After that we will take a deep dive into the foundations of distributed data storages and data processing as well as the belonging concepts and challenges of reliability, scalability, replication, partitioning, batch and stream processing. Later on we will take a look at the most common used software and frameworks (mostly the Hadoop and Spark ecosystem). At the end, as you know the basic concepts and you are able to setup and work with distributed environments and huge data sets, there will be a short introduction to data science.

Materials: Script | Slides | Exercises | Solutions | Docker Files | DockerHub | Git

Big Data

Winter Semester 2023/2024

This lecture will give you a brief introduction to so what is called ’Big Data’. We will quickly refresh the basics about databases, data models and data processing you have learned so far and compare those to the distributed world of Big Data. After that we will take a deep dive into the foundations of distributed data storages and data processing as well as the belonging concepts and challenges of reliability, scalability, replication, partitioning, batch and stream processing. Later on we will take a look at the most common used software and frameworks (mostly the Hadoop and Spark ecosystem). At the end, as you know the basic concepts and you are able to setup and work with distributed environments and huge data sets, there will be a short introduction to data science.

Materials: Script | Slides | Exercises | Solutions | Docker Files | DockerHub | Git

Big Data

Winter Semester 2022/2023

This lecture will give you a brief introduction to so what is called ’Big Data’. We will quickly refresh the basics about databases, data models and data processing you have learned so far and compare those to the distributed world of Big Data. After that we will take a deep dive into the foundations of distributed data storages and data processing as well as the belonging concepts and challenges of reliability, scalability, replication, partitioning, batch and stream processing. Later on we will take a look at the most common used software and frameworks (mostly the Hadoop and Spark ecosystem). At the end, as you know the basic concepts and you are able to setup and work with distributed environments and huge data sets, there will be a short introduction to data science.

Materials: Script | Slides | Exercises | Solutions | Docker Files | DockerHub | Git

Big Data

Winter Semester 2021

This lecture will give you a brief introduction to so what is called ’Big Data’. We will quickly refresh the basics about databases, data models and data processing you have learned so far and compare those to the distributed world of Big Data. After that we will take a deep dive into the foundations of distributed data storages and data processing as well as the belonging concepts and challenges of reliability, scalability, replication, partitioning, batch and stream processing. Later on we will take a look at the most common used software and frameworks (mostly the Hadoop and Spark ecosystem). At the end, as you know the basic concepts and you are able to setup and work with distributed environments and huge data sets, there will be a short introduction to data science.

Materials: Script | Slides | Exercises | Solutions | Docker Files | DockerHub | Git

Big Data

Winter Semester 2019/2020

This lecture will give you a brief introduction to so what is called ’Big Data’. We will quickly refresh the basics about databases, data models and data processing you have learned so far and compare those to the distributed world of Big Data. After that we will take a deep dive into the foundations of distributed data storages and data processing as well as the belonging concepts and challenges of reliability, scalability, replication, partitioning, batch and stream processing. Later on we will take a look at the most common used software and frameworks (mostly the hadoop ecosystem). At the end, as you know the basic concepts and you are able to setup and work with distributed environments and huge data sets, there will be a short introduction to data science.

Materials: Script | Slides | Exercises | Solutions | Docker Files | DockerHub | Git

Big Data

Winter Semester 2018/2019

This lecture will give you a brief introduction to so what is called ’Big Data’. We will quickly refresh the basics about databases, data models and data processing you have learned so far and compare those to the distributed world of Big Data. After that we will take a deep dive into the foundations of distributed data storages and data processing as well as the belonging concepts and challenges of reliability, scalability, replication, partitioning, batch and stream processing. Later on we will take a look at the most common used software and frameworks (mostly the hadoop ecosystem). At the end, as you know the basic concepts and you are able to setup and work with distributed environments and huge data sets, there will be a short introduction to data science.

Materials: Script | Slides | Exercises | Solutions | Docker Files | DockerHub | Git

About Me

DataWhizz Gmbh & Co. KG

Co-Founder
Director Architecture and Development
Data is our passion. We Love crunching data and building enterprise-ready, scalable data-driven products.

www.datawhizz.io

Apr 2018 - now

Cooperative State University

Baden-Wuerttemberg
University Lecturer, Faculty Of Computer Science
Lecturing in the fields of Big Data, data engineering, data science, development and architecture of data-intensive applications.

www.dhbw-stuttgart.de

2018 - now

ProSiebenSat.1 Media SE

Data Competence Center
Head of Data Architecture and Development
Technical lead for data-driven projects of ProSiebenSat.1 Media SE data initiative.

www.prosiebensat1.com

Jan 2014 - Nov 2018

IBM Global Business Services

DWH, BI&Analytics, BigData, Application Development
IT-Architect
Working for several client projects in field of Datawarehousing, Business Intelligence, Analytics & Reporting as well as BigData.

www.ibm.com

Oct 2009 - Dec 2013