Data Science meetup | Crunch edition

Location image of event venue

Details

This is a free event, starting at 6pm.

// GOOD TO KNOW

If you are also interested in Crunch Conference (Oct 16-18), use the "BPDS" coupon code to get $85 off regular or late bird tickets at https://crunchconf.com/

// SCHEDULE

6:00pm - Doors open
6:10pm - Pizza and beers
6:30pm - Talks

// TALKS

DATA - THE "FUEL" OF SELF-DRIVING CARS
by Sándor POGÁCSÁS
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The development of real-world fully automated driving systems is impossible without data driven algorithms. The training and evaluation of these machine learning and deep learning models needs efficient data pipelines. The talk will outline the life cycle of data in the development process of self-driving cars and how data engineering plays a role in this.

Sándor works as Lead Artificial Engineer at Bosch.

CONSUMER OBSESSION: HOW THE DATA-DRIVEN CULTURE @ Runtastic CHANGES THE GAME FOR adidas
by Christoph FERRARI
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In 2019 adidas and Runtastic intent to take the sport apparel market to the next level.
It's not enough any more to simply sell running shoes.
You also need to be able to tell a compelling story and you need to be able to engage your customer outside the shop to build long-term loyalty.
In their combined obsession about the user, adidas and Runtastic are developing new business cases and a next-level digital experience to engage users with their products and services.
A key success factor for this is the data-driven culture at Runtastic, that not only enables product teams to develop better experiences but furthermore creates the foundation for building new business cases for adidas.
This talk will explain the steps already taken, the success factors and pitfalls that were encountered and the next steps ahead.
The audience can learn from this insights in case they are facing a similar transition within their company / market and therefore potentially move even faster.

Christoph is the Head of Data Engineering and Data Science at Runtastic.

MONITOR YOUR DATA, NOT JUST YOUR PIPELINES
by Jean-Mathieu SAPONARO
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It has become standard practice for data engineering teams to monitor their data pipelines and infrastructure. But end-users, data analysts, data scientists, and everyone else within your company use the data itself that is produced by those pipelines. And they are making big decisions based on it. That is why continuously monitoring these data sets and making sure that you are alerted of any issue is crucial.
In this talk, I will detail why you want to add observability on your data itself, what any data engineering team can monitor, how to instrument this monitoring, and even how to make the data self-heal.

Jean-Mathieu is a Data Engineer and the Internal Analytics Application team lead at Datadog.