AMLD 2024 - Data Engineering Ninja Workshop

In our workshop, we'll delve into real-world data engineering problems and provide practical exercises for attendees.

March 23, 2024 9:00
March 23, 2024 12:30
SwissTech Convention Center

Data Engineering Ninja - Level 1

Data engineering is the achilles heel of data teams in most organisations today. We will introduce you to three frequently occurring types of data engineering issues using some real-world stories.

The participants will be invited to solve concrete problems using the datasets we provide. Coaching, hints and pop quizzes will be provided throughout.

The outcome for participants is an appreciation of data engineering, and practical knowledge on how to structure data to answer your questions.

What to expect:

▪ An exploration of common data engineering issues through case studies.

▪ Hands-on problem-solving with provided datasets. Feel free to use any data analysis tool you're comfortable with (e.g., Excel, Python, R).

▪ A better understanding of data engineering principles and how to apply them to your work.


Fatima Soomro
Head of Operations

Fatima Soomro brings a wealth of experience to her role as an instructor, with a background in operations leadership at Argusa and extensive expertise in data analytics. Her career includes consulting roles at ELCA Informatique and Argusa SA. Her academic background includes research in particle physics at the Imperial College London, EPFL and INFN, and notable contributions to high-profile analyses at CERN.

Her diverse experience, spanning academic research to practical data applications, equips her with a unique perspective on data's role in strategic decision-making and innovation.

Luca Pescatore
Head of Technology

Luca Pescatore is Argusa's Head of Technology, leveraging his deep expertise in data analytics and technology to drive strategic company initiatives. In his role at Argusa, Luca Pescatore, consults, administers IT infrastructure, and provides Tableau training. His expertise spans data modeling, analysis, and visualization, applied across diverse industries.

His background includes impactful research and data science work at CERN and teaching positions, showcasing a blend of academic excellence and practical industry application.


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