Top 10 Data Engineering Mistakes

A large fraction of big data projects fail to deliver return on investment or take years before they do so. Join us at our second meetup “Top 10 data engineering mistakes” on 22 May and hear what challenges could be waiting for you in the field of big data and how to deal with them.

The reasons of failure are typically a combination of project management, leadership, organization, available competence and technical failures. In this meetup we will focus on the technical aspects and present the most common or costly data engineering mistakes are being experienced when building scalable data processing technology, as well as advice for how to avoid them.

This meetup will be hosted by Gintaras Sakalas, data lake team manager, and our guest from Stockholm, Lars Albertsson, an independent consultant, specializing in scalable data processing solutions and assisting SEB with data processing architecture, data engineering education and agile methodologies. Lars Albertsson has vast experience having worked with data-intensive and scalable applications at Google, Spotify and other companies.

In his presentation Lars will share his experience with us and tell us some war stories from large scale production environments, some that lead to reprocessing of petabytes of data or DDoSing critical services with a Hadoop cluster, and what was learnt from the incidents.

Seats for participants are limited, so be sure to grab your seat now!

The meetup will be held in English.

Light food and drinks will be served.