BIG DATA CONFERENCE

EUROPE 2022

November 21-24

Vilnius and Online

Confirmed Talks

Andrej Baranovskij

Katana ML, Lithuania

MLOps: Scaling TensorFlow Model on Kubernetes

ML model serving/prediction API can be scaled on Kubernetes by adding or removing Pod instances. With a live demo, we will explain how scaling can be done for TensorFlow (applicable to PyTorch) model running on Kubernetes.

Session Keywords
🔑 MLOps
🔑 Python

Jesse Anderson

Big Data Institute, Portugal

Foundations of Data Teams

This talk will cover the importance of a solid foundation and what management should do to fix it. To do this Jesse will be sharing a real-life analogy to show how we can be misled and what that means for our success rates.

Session Keywords
🔑 Management
🔑 Teamwork
🔑 Data Science
🔑 Data Engineering

Steve Upton

Thoughtworks, Germany

You Are Overthinking Data Quality

This talk explores the real challenges around ensuring data quality and identifies a critical element that is missing from many popular approaches to data quality. We will also look at how lessons from Product Thinking, Data Mesh and Site Reliability Engineering can help us in our quest for data quality.

Session Keywords
🔑 Data Quality
🔑 Data Mesh
🔑 Product Thinking

Timothy Spann

StreamNative, US

FLiP Into Pulsar Apps

In this session, Timothy will introduce you to the world of Apache Pulsar and how to build real-time messaging and streaming applications with a variety of OSS libraries, schemas, languages, frameworks, and tools.

Session Keywords
🔑 Pulsar
🔑 Flink
🔑 NiFi

Vsevolod Dyomkin

Franz, Ukraine

Text2graph – A Practical Approach to Transforming Free-Form Text Into a Computable Graph Structure

In this talk, we describe a novel hybrid ML/symbolic approach to transforming natural language sentences into RDF graph structures, as well as possible practical applications of the results in downstream tasks, such as question answering, text entailment, and others.

Session Keywords
🔑 Natural Language Processing
🔑 Graph Databases

Data Horizons With Postgres

This talk explains why data needs have changed, and how Postgres has uniquely adjusted to those needs. The talk also explains how to store data outside of Postgres while maintaining integrated data management.

Session Keywords
🔑 Postgres
🔑 Microservices
🔑 Data Governance

Dipti Borkar

Ahana, Presto Foundation, US

Talk, Extra-Talk Presto 101: An Introduction to Open Source Presto

In this session, Dipti will introduce the Presto technology and share why it’s becoming so popular – in fact, companies like Facebook, Uber, Twitter, Alibaba, and much more use Presto for interactive ad hoc queries, reporting & dashboarding data lake analytics, and much more. We’ll also show a quick demo on getting Presto running in AWS.

Session Keywords
🔑 Open Source
🔑 Data Management
🔑 Presto
🔑 SQL

Gad Salner

Melio, Israel

How to Scale a Unicorn-Building Engineering Team (And Stay Sane)

In this talk, Gad will take a deep dive into our new strategy step-by-step, from planning to execution: his structured game plan for empowering engineers to drive your team’s rapid growth in size, responsibility, and impact.

Session Keywords
🔑 Team building
🔑 management
🔑 processes
🔑 culture
🔑 agile

Kuba Misiorny

Untrite, UK

Developing Intuition For AI As A Leader: Path To Data Literacy

Developing such intuition is a critical role of a leader, that strongly correlates with the company’s success. During this presentation, Kuba is going to give you a seed of this intuition by going a little bit deeper than most of the “executive guides to AI”.

Session Keywords
🔑 Technology
🔑 Leadership
🔑 AI

Nir Barazida

DagsHub, Israel

Notebook To Production

Should we just throw our Jupyter Notebooks out the window and move to classic IDEs? Probably not – Jupyter Notebooks are, after all, a great tool that gives us superhuman abilities. We can, however, be more production-oriented when using them. How does this look in practice? That is exactly what we’ll cover in this talk.

Session Keywords
🔑 Experiment Tracking
🔑 Data Versioning
🔑 Jupyter Notebook
🔑 MLOps