Online Edition

September 28-30


Confirmed Talks

Juan Venegas

Growth Tribe, The Netherlands

Translating Data Into Powerful Stories

In this live session, we will dive into the fundamentals of data storytelling & visualisation. We’ll borrow tried-and-tested techniques from master presenters. We’ll go on a journey from plotting our story to designing our slides, infusing new life into our data without fabricating lies or boring our audiences.

Session Keywords
🔑 Data storytelling
🔑 Data Visualisation

Alex Sanginov

ServiceNow, US

Embracing #AiFirst Enterprise-Wide

How do you change perceptions to embrace AI enterprise-wide?
Where do you even begin? How do you keep the momentum? And most importantly, How do you maintain the hype while delivering results that people love?!

Session Keywords
🔑 ML
🔑 Enterprise AI
🔑 Data Science

Mark Grover

Stemma, US

Trust Your Data

In this talk, Mark will why trust in data matters to the data industry and the tactics best-in-class organizations use to address it — including org structure, culture, and technology.

Session Keywords
🔑 Data Discovery
🔑 Metadata
🔑 Amundsen

Phil Winder

Winder Research, UK

A Code-Driven Introduction to Reinforcement Learning

Although this presentation is suitable for beginners, you will benefit if you have some exposure to data science and machine learning.

Session Keywords
🔑 Reinforcement Learning
🔑 Cyber Security

Albert Lewandowski

GetInData, Poland

Best Practices for ETL with Apache NiFi on Kubernetes

During the talk, there are described all details about migrating pipelines from the old Hadoop platform to the Kubernetes, managing everything as the code, monitoring all corner cases of NiFi and making it a robust solution that is user-friendly even for non-programmers.

Session Keywords
🔑 NiFi
🔑 Kubernetes

Bas Geerdink

Aizonic, The Netherlands

The State of MLOps – Machine Learning in Production at Enterprise Scale

In this session, we’ll explore this relatively new subject. Bas will explain the need for MLOps (and AIOps and ModelOps which are related), dive into the tools and techniques, and give some examples of real-world solutions.

Session Keywords
🔑 MLOps
🔑 Big Data
🔑 Machine Learning

Carlos Manuel Duclos-Vergara

Schibsted, Norway

Choosing the Right Abstraction Level for Your Kafka Project

What kind of operations need to be applied to the events? Do we need to interact with external systems? In this presentation, he will go through several scenarios and cases to highlight the key factors that should be considered when deciding which API should be used for a given project.

Session Keywords
🔑 Streaming Architecture
🔑 Event Processing
🔑 Kafka

Daniel Wrigley

SHI, Germany

Keyword Search is Dead! And so are Solr and Elasticsearch?

How can AI combined with Vector Similarity Search efficiently deliver more relevant search results than conventional methods?
For which cases is there an economic gain from their application?
To answer these and other questions, he will provide an overview of the current state and an outlook into the future possibilities of new technologies and reveal how search applications can get a boost with the help of AI. 

Session Keywords
🔑 Natural Language Processing (NLP)
🔑 Vector Similarity Search
🔑 Elasticsearch
🔑 Solr

Frank Munz

Databricks, Germany

Share Massive Amounts of Live Data with Delta Sharing

The proposed session is a technical session for developers and big data architects. The session includes a live, hands-on demonstration of Delta Sharing. A detailed explanation of how to get started with purely open source is provided to the interested audience.

Session Keywords
🔑 Data Science
🔑 Open Source
🔑 Data Sharing

Einat Orr

Treeverse, Israel

Rethinking Ingestion: CI/CD for Data Lakes

What they propose and will cover in this talk, is a new strategy for data lake ingestion. One where new data can be added in isolation then tested and validated, before “going live” in a production table. Finally, they will show how git-for-data tools like lakeFS and Nessie enable this ingestion paradigm in a seamless way.

Session Keywords
🔑 Data Lake
🔑 Data Versioning
🔑 Ingestion