Big Data Days 2021

Online Edition

28-30 Cентября

онлайн

Доклады

Federico Fregosi

VP of Engineering

UK, Contino

Talk

Architecture vs. Operating Model – A Cloud Conundrum

In this talk, we will cover our experience liberating the data in the mainframe with a hybrid serverless/containerized solution built on AWS. We will dedicate a special section to performance optimizations done to reduce the cold start problems and support aggressive performance targets.

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Mainframe
Serverless
Data Streaming

Kathrin Melcher

Data Scientist

Germany, Knime

Talk

A Friendly Introduction to Codeless Deep Learning

In this talk, you’ll first get a basic introduction to neural networks, the concepts behind training them, and how to build and train a DL model without needing a single line of code using the Keras integration of the KNIME Analytics Platform. Once you are familiar with the basics we will move on to convolution neural networks, for image processing.

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Deep Learning
CNN
Keras
KNIME

Paweł Skrzypek

Chief Technology Officer

Poland, AI Investments

Anna Warno

Data Scientist

Poland, AI Investments

Talk

Complex AI Forecasting Methods for Investments Portfolio Optimization

Presentation of the first complete AI investment platform. It is based on the most innovative AI methods: most advanced neural networks (ResNet/DenseNet, LSTM, GAN autoencoders) and reinforcement learning for risk control and position sizing using the Alpha Zero approach.

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ML
Forecasting
Investing

Paweł Skrzypek

Chief Technology Officer

Poland, AI Investments

Talk

Complex AI Forecasting Methods for Investments Portfolio Optimization

Presentation of the first complete AI investment platform. It is based on the most innovative AI methods: most advanced neural networks (ResNet/DenseNet, LSTM, GAN autoencoders) and reinforcement learning for risk control and position sizing using the Alpha Zero approach.

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ML
Forecasting
Investing

Anna Warno

Data Scientist

Poland, AI Investments

Valentina Djordjevic

Head of Data Science

Serbia, Things Solver

Talk

Building Data Science Products

She will be talking about the challenges in building this kind of platform, switching from service-oriented data science teams to product-oriented teams, changing the mindset, biggest problems encountered, and how we managed to tackle growth, client pressure, data science, heuristics, and algorithms under the same umbrella.

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ML
Data Science
Product Development

Gad Salner

Group Manager

Israel, Melio

Talk

Zoom Out: Building a Kickass Engineering Team Remotely

In this talk, Gad outlines how to build a winning engineering team and overcome remote-work challenges such as communication, engagement, development velocity, cultural gaps, and more. He explains the importance of calibrating your team’s efforts and processes, emphasizes the importance of high-trust communication, and curating the right cultural and technical framework for your team.

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Team Management
Agile

Herminio Vazquez

Machine Learning Consultant

Mexico, IOVIO

Talk

The Unbreakable Data Pipeline

This session, will provide, detailed examples on the engineering aspects of authoring and maintaining high-quality data pipelines using Apache Spark and Delta Lake. Optimizations for performance gains, tricks that reduce verbosity, caveats, and trade-offs, standards in a team, and all those little things you wish have known before your project started…

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Data Engineering
Data Pipeline
PySpark

Mario A Vinasco

Director of Analytics

US, Credit Sesame

Talk

The Intuition Behind Machine Learning In Marketing

This talk presents the key insights that make AI/ML useful for marketing and demystifies the core technology and illustrates case studies where my team applied the technology. In this talk, he will discuss how predictive models are used across these areas

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ML
Marketing
Advanced Segmentation
Cross Sell Predictions

Marta Paes

Senior Developer Advocate

Germany, Materialize

Talk

An Introduction to Streaming SQL with Materialize

In this talk, we’ll introduce Materialize, a streaming database that lets you use standard SQL over streams of data and get low-latency, incrementally updated answers as the underlying data changes. We’ll cover the basic concepts of streaming SQL and highlight what makes Materialize unique in comparison to other tools, then tie it all together by building a simple streaming analytics pipeline — from data ingestion to visualization!

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Databases
Streaming SQL

Александр Дмитриев

Директор по Продажам

Россия, ADV LaunchPad

Talk

Как Начать Продажи Big Data Продукта с Нуля: Три Обязательных Составляющих

Если выручка в компании растет, часто, на департамент продаж не обращают внимание. А когда выручка в компании выходит на плато или падает, часто причину ищут именно в продажах. Что примечательно, и в первом и во втором случае в организации продаж может быть как всё очень плохо, так и наоборот, точки роста могут лежать за пределами функции продаж. Давайте разбираться, как правильно организовать продажи сложных решений с нуля.

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Big Data Products
Sales

Paško Pajdek

Head of Engineering

Croatia, Mediatoolkit

Talk

Designing Robust Processing System With Redis

If you want to know how we built our system with mechanisms such as queueing, scheduling, and backpressure implemented with Redis, come, listen and discuss.

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Realtime Data Processing
Queueing
Redis

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