GOTO Night with Emily Gorcenski
Online GOTO Night

GOTO Nights are a series of community meetups that cover a variety of tech topics by our industry's top creators, builders and thought leaders.

Each event includes an educational and inspirational talk paired with a Q&A and a chance for attendees to network with like-minded developers in a casual environment.

Thursday Oct 28
17:00 –
18:00
CET
Zoom

GOTO Night with Emily Gorcenski

Join us for the GOTO Night "Shifting Left to Improve Data Reliability with SLO Theory" with Emily Gorcenski. This GOTO Night is focused on ways to shift left with data through a tool-agnostic lens, and how this approach moves us closer to federated and decentralized data architectures like Data Mesh.

Date: October 28
Time: 5:00pm - 6:00pm CEST
Location: Zoom

Agenda

5:00pm - Welcome to this GOTO Night with Emily Gorcenski
5:05pm - Emily Gorcenski will present her subject of the day
5:30pm - Live Q&A with Emily Gorcenski
5:55pm - Thank you for joining us for this GOTO Night

Abstract

The tools and patterns for data engineering have improved significantly over the past several years, but the challenges around getting value from data have stayed the same. Business stakeholders continue to report that issues with data quality, data trustworthiness, and data discoverability are blocking the ability to meaningfully materialize value from data assets within a company. What leads to these patterns, and what do we have to do differently to address these challenges?

Borrowing the "shift left" approach to quality, security, and governance from the continuous delivery world, we can build better, more reliable data pipelines and systems. Using SLO theory, we'll look at ways to shift left with data through a tool-agnostic lens, and how this approach moves us closer to federated and decentralized data architectures like Data Mesh.

About the speaker

Emily has over ten years of experience in scientific computing and engineering research and development. She has a background in mathematical analysis, with a focus on probability theory and numerical analysis. She is currently working in Python development, though she has a background that includes C#/.Net, Unity3D, SQL, and MATLAB. In addition, she has experience in statistics and experimental design, and has served as principal investigator in clinical research projects.

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