Better Code for Data Science

Essential success factors for making Data Science work.

Proper engineering is a key success factor for Data Science and AI in production.

Python offers several ways to achieve the required quality level for a successful implementation.
Beyond writing quality code, there are other aspects to consider such as personas, standardization and architecture

Presented at the PyData Global 2020 on Nov 12, 2020. PyData Global , one of the largest gathering of the data science and AI community worldwide.

The talk outlines the many aspects as:

  • Principles for Data architecture, coding and deployment.
  • Provides definitions of what makes code good or bad, pitfalls and anitpatterns.
  • Workflows
  • Programming skills matter for quality assurance
  • Personas / backgrounds that have to be on the same page

Key Takeaways & Use Case Presented

Open Source Community

We care about Open Source Software and the community - it's give-and-take. Since 2017 Königsweg is a community sponsor of PyConDE and founding sponsor of the local Südwest and Frankfurt meetups. Interested? Maybe drop by one day! Everyone is welcome!

Major yearly international confernce, join us for the next PyConDE & PyData Berlin conference in 2021.

conference website

Regular meetup with more than 1000 members in Karlsruhe, Mannheim and Heidelberg.

join via Meetup

Regular meetup with more than 1000 members in Frankfurt with a slight focus on financial.

join via Meetup

Your Contact Person
Alexander Hendorf -
Managing Partner

Alexander Hendorf is a renowned IT professional and expert in Big Data, Data Mining, Machine Learning and Artificial Intelligence. He is a frequent speaker at international conferences like PyData, PyCons or MongoDB World NYC.
After founding an independent label, Hendorf recognized the potential of digitalization for the music industry and began programming trading platforms and databases.
This combination of entrepreneurship and digitization is reflected in his consulting concepts. With a high level of expertise, he specializes in particular in process optimization through Agile Data Analytics and Data Value Assessments.

Hendorf is a Python Software Foundation Fellow, one of the chair persons of PyConDE and PyData Berlin, chair person of the German Python Softwareverband e.V and one of the 25 MongoDB Masters worldwide. Through his commitment to open source and his membership in corresponding global organizations, he also has an excellent international IT network.