Big Data Days 2019

 October 8-10   Moscow

SCHEDULE

Workshops
(8th October)
Date: 8th October, 2019.
Time: 10:00-17:00
Doors open at 9:00.
Place: Digital October, Bersenevskaya Naberezhnaya 6с3, 4th floor, Moscow
  • By buying a ticket you receive admission to only one workshop of your choice.
  • Every workshop lasts for whole day. All workshops are held at the same time, therefore by buying a ticket you can participate in only one workshop of your choice. You cannot change your choice of a workshop. Language of a workshop depends on the speaking language of the trainer.
  • Language of each workshop is noted on each card.
  • There will be no simultaneous translation during workshops, but, taking into account previous experience, all trainers are aware of the language barrier and are going to put in as much effort as possible to ease the understanding of the theme.
  • Each participant has to have a personal notebook on him.

Data culture as a part of digital transformation – challenges and solutions (RU)

SOLD OUT

Mikhail Petrov
Счетная палата Российской Федерации

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1st Conference Day
(9th October)

Simultaneous interpretation will be provided in Hall #2.

Time Hall 1 Hall 2 Hall 3
09:00 - 10:00 Registration
10:00 - 10:10 Opening of the conference
10:10 - 11:05
OPENING KEYNOTE:
Data Science for Lazy People, Automated Machine Learning (EN)
Diego Hueltes
RavenPack
Hall 1
11:15 - 12:00 How to increase A/B convergence time 10-100 times (RU)
Valeriy Babushkin
X5 Retail Group/ Yandex
A/B Testing
Bayes
Linearization
Machine Learning
Hall 1
What it takes to build production ready AI solution (EN)
Nenad Bozic
SmartCat
AI Solution
Hall 2
Big Data on Kubernetes (EN)
Maciej Bryński
Payability
Hadoop
Kubernetes
Kafka
Spark
Hall 3
12:00 - 12:15 Coffee Break
12:15 - 13:00 How to Ensure the Work of the Data-Model of a Business (RU)
Denis Emelyantsev
McKinsey & Company
Data Science
Big Data
Sustainability
Financial Effect
Hall 1
Big Data as a Fuel for Economy of Impressions (RU)
Yulia Bogachyova
QIWI
Big Data
Personalization
Hall 2
The Semiotic Analysis of Legal texts (RU)
Vladimir Krylov
Artezio
Natural Language Understanding
Semiotic Analysis
Hall 3
13:00 - 14:00 Lunch
14:00 - 14:45 ML Pipeline: Structuring Data Analysis Projects (RU)
Kirill Vasin
SEMrush
Data Version Control
Teamwork
Hyperparameter Optimisation
Hall 1
Data Science as a Service (EN)
Arno Broekhof
Dataworkz
Serverless
Machine Learning
Cloud
Hall 2
How to build the career transformation road map in Big Data (RU)
Elena Gerasimova
Netology
Career
Transformation
Road Map
Hall 3
14:55 - 15:40 Deep Learning Applied to Failure Management in Apache Spark (ENG)
Guglielmo Iozzia
MSD
Machine Learning
Hall 1
Advanced (elastic) search for your legacy application (EN)
David Pilato
elastic
Search
Data
Elasticsearch
Opensource
💻 Live coding
Hall 2
A head start on Cloud-native Event Driven Applications (EN)
Sriskandarajah Suhothayan
WSO2
Stream Processing
Kubernetes
Event Driven Applications
Hall 3
15:40 - 16:00 Coffee Break
16:00 - 16:45 Key tips for successful Data Science project (RU)
Vladimir Dmitriev
Visiology
Data Science in Manufacturing
Project Management
Hall 1
Introducing the new Cloudera Data Platform. From the Edge to AI (EN)
Gergely Devenyi
Cloudera
Big Data
Hybrid Cloud
Multifunction
Secure
Analytics
Cloud
Hall 2
Mass Scoring in CRM – Secrets and Pitfalls (RU)
Aleksandr Serbul
1C-Bitrix
Crm
Scoring
Classification
Logistic Regression
Predictive Marketing
Hall 3
16:55 - 17:40 Data-driven Cases for Business Amplification in Modern Digital Banking (RU)
Nikita Pustovoytov
BCS
Machine Learning
Scoring
Banking
Hall 1
On board Artificial Intelligence : train, deploy and use Deep Learning on an edge device, a Raspberry Pi (EN)
Constant Bridon
OCTO TECHNOLOGY
Deep Learning
Raspberry
Hall 2
Fault-Tolerance and Load Balancing for Your MySQL Backend (RU)
Vlad Fedorkov & Anastasia Raspopina
ProxySQL
High Load
MySQL
Hall 3
17:50 - 18:35 Building Enterprise Data Platforms Based on Open Source (RU)
Sergey Zolotarev
Arenadata
Open Source
Hall 1
AI in Banking (RU)
Andrey Leushev
Farzoom
Banks
AI
Cross-Sale
Hall 2
TBA
Hall 3
2nd Conference Day
(10th October)

Simultaneous interpretation will be provided in Hall #2.

Time Hall 1 Hall 2 Hall 3
09:00 - 10:00 Registration
10:00 - 10:10 Opening of the second conference day
10:10 - 11:05 Big Data Integration: ETL, ELT, Data Lake, Data Mesh – part I (RU)
Alexander Breyman
Luxoft Training
Data Mesh
Data Lake
ETL
💻 Notebook needed
👷 Workshop
Hall 1
Real time Data Pipelines using Spark Streaming (EN)
Yulia Stolin
Outbrain
Spark Streaming
Kafka
Lambda Architecture
Hall 2
Do Androids Dream of Electric Guitars? How I Taught Neural Network to Compose Music (RU)
Andrey Shagalov
Artezio
Music
Machine Learning
Google Magenta
Hall 3
11:15 - 12:00 Big Data Integration: ETL, ELT, Data Lake, Data Mesh – part II (RU)
Alexander Breyman
Luxoft Training
Data Mesh
Data Lake
ETL
💻 Notebook needed
👷 Workshop
Hall 1
Who needs Data Governance? (EN)
Milos Milovanovic
Things Solver
Data Management
Data Governance
Advanced Analytics
Hall 2
Sample size estimation and machine learning model selection (RU)
Vadim Strijov
MIPT State university
Machine Learning
Sample Size Estimation
Model Selection
Hall 3
12:00 - 12:15 Coffee Break
12:15 - 13:00 Data Science Toolbox: Sklearn and Beyond (RU)
Maxim Panteleev
Luxoft Training
Python
Scikit-learn
Hall 1
Distributed Deep Learning with Keras and TensorFlow on Apache Spark (EN)
Guglielmo Iozzia
MSD
Keras
TensorFlow
Apache Spark
Distributed Deep Learning
Hall 2
Bringing Big Data to People Inside a Huge Investment Bank: How We Built Business Intelligence on Clickhouse with Row-Level Security (RU)
Pavel Yakunin & Denis Goihburg
Deutsche Bank Technology Center
Clickhouse
Business Intelligence
Data Access Control
Hall 3
13:00 - 14:00 Lunch
14:00 - 14:45 Building Large Tarantool Cluster with 100+ Nodes (RU)
Yaroslav Dynnikov
Tarantool, Mail.Ru Group
Tarantool
Orchestration
Horizontal scaling
Hall 1
Big “Serverless” Data (EN)
Eric Johnson
Amazon Web Services
AWS
Serverless
Hall 2
Home Credit: Our Road to Data Driven (RU)
Vladimir Bogdanovskiy
Home Credit Bank
Big Data
Cloudera
Data Lake
Hall 3
14:55 - 15:40 What to begin the client data analysis with and how not to get lost in Big data (RU)
Sergey Shopik
Customer Experience Laboratory
Data Analysis
Job Segmentation and Personalisation
Hall 1
Disrupting Data Discovery at Lyft with Amundsen (EN)
Philippe Mizrahi
Lyft
Open Source
Data Discovery
GDPR
Hall 2
Data Science & AI: Infrastructure Matters (EN)
Kelly Schlamb
IBM Canada Ltd.
Data Science
Infrastructure
Hall 3
15:40 - 16:00 Coffee Break
16:00 - 16:45 Integrating Small Data, Synthetic Data in AI Strategy for Fashion Retail (RU)
Andrey Golub
ELSE Corp Srl
Small Data
Recommendation Systems
Fashion
Hall 1
Breaking out the lead scoring algorithm (EN)
Valentina Djordjevic
Things Solver
Data Science
Lead Scoring
Hall 2
From neural networks to outsmarting the local authorities (EN)
Bogdan Ivtsjenko
Dataworkz
Real Time
Object Detection
Hall 3
16:50 - 17:20
QUIZ
17:20 - 18:15
CLOSING KEYNOTE:
Managing Your Black Friday Logs (ENG)
David Pilato
elastic
Hall 1
18:15 - 18:20
Closing of the conference