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UID:pretalx-pycones-2023-YZ3TU3@charlas.2023.es.pycon.org
DTSTART;TZID=GMT:20231006T174500
DTEND;TZID=GMT:20231006T191500
DESCRIPTION:Data engineering has experienced enormous growth in recent year
 s\, allowing for rapid progress and innovation as more people than ever ar
 e thinking about data resources and how to better leverage them. In this t
 utorial\, we will build an end-to-end modern data platform for the analysi
 s of medical data using open-source tools and libraries.\n\nWe will start 
 with an overview of the platform components\, including data warehousing\,
  data integration\, data transformation\, data orchestration\, and data vi
 sualization. We will then dive into each component\, exploring the technol
 ogies and tools that make up the platform.\n\nWe will review Python-based 
 tools such as DBT\, Apache Airflow\, Openmetadata\, and Querybook to build
  the platform. We will walk through the process step-by-step\, from creati
 ng a data lake to integrating data from multiple sources\, transforming th
 e data\, orchestrating data workflows\, and visualizing the data.\n\nAtten
 dees will benefit from this tutorial if they are interested in learning ho
 w to build an end-to-end modern data platform for biomedical data using Py
 thon-based tools. They will also benefit from learning about the open-sour
 ce tools and libraries used in the tutorial\, which they can then apply to
  their own data engineering projects.\n\nTime breakdown:\n\n    Introducti
 on and overview (20 minutes)\n    Data integration (20 minutes)\n    Data 
 transformation (20 minutes)\n    Data visualization (20 minutes)\n    Q&A 
 (10 minutes)\n\nCheck the workshop materials https://github.com/bsc-health
 -data/pycones-23-modern-data-stack and install the requirements in advance
  for a better experience
DTSTAMP:20260411T055250Z
LOCATION:Salón Grados
SUMMARY:Building an End-to-End Open-Source Modern Data Platform for Biomedi
 cal Data - Alberto Labarga
URL:https://charlas.2023.es.pycon.org/pycones-2023/talk/YZ3TU3/
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