Check the ONSITE conference location: LOCATION

 

In this year's edition of the conference, we will focus on the areas:
Artificial Intelligence and Data Science, Streaming and Real-Time Analytics,
Data Strategy and ROI, Data Engineering, Architecture Operarations &Cloud.

 


26.04.2022 - WORKSHOP DAY

9.00 - 16.00

PARALLEL WORKSHOPS (independent workshops, paid entry) | on-site, WARSAW

Introduction to Machine Learning Operations (MLOps)

 

DESCRIPTION:

SESSION LEADER:

Machine Learning Engineer
GetInData

Real-Time Stream Processing

 

DESCRIPTION:

SESSION LEADERS:

Data Engineer
GetInData
Software developer
GetInData

Modern data pipelines with dbt

 

DESCRIPTION:

SESSION LEADER:

Software/Data Engineer
GetInData

19.00 - 22.00

EVENING SPEAKERS MEETING (Only for Speakers) on-site, WARSAW

 

 

27.04.2022 - 1ST CONFERENCE DAY | HYBRID: ONLINE + ONSITE

 

8.30 - 9.00

Morning cofee and networking time

9.00 - 9.10

Sesja plenarna
Conference opening
CEO & Meeting Designer
Evention
CEO and Co-founder
GetInData

9.10 - 11.25

PLENARY SESSION

9.10 - 9.30

Plenary Session
Big data at Microsoft: The story behind the tech that powers an exabyte-scale data lake

Speaker:

Group Product Manager – Azure Engineering
Microsoft

9.30 - 9.55

KEYNOTE PRESENTATION

Plenary Session
Data Mesh in Practice - How to set up a data driven organization

Speaker:

Data Engineering Manager
Zalando

9.55 - 10.10

BREAK

10.10 - 10.35

Plenary Session
And then the magic happens: 9 ways to put your big data platform migration at risk

This session offers learnings from multiple big data platform migration engagements that involved Google's Professional Services organization. Each presented customer case had different constraints, necessitating a variety of approaches to ensure success despite critical risks to the deadline.

Data SCE at Professional Services Organization
Google Cloud Poland
Cloud Customer Engineering Manager
Google Cloud Poland

10.35 - 11.00

Plenary Session
Why data analytics is critical for business at Kambi
Data Platform Architect
Kambi

11.00 - 11.25

Plenary Session
Oh my god Hybrid Cloud! Two or more data architectures fused together, how?

Speaker:

Solutions Engineer
Cloudera

 

Solutions Engineer
Cloudera

11.25 - 11.50

BREAK

11.50 - 13.20

PARALLEL SESSIONS

Host:

BigData Engineer
GetInData

Host:

Data Engineer
GetInData

Host:

Senior Cloud Data Engineer
GetInData

11.50 - 12.20

Data Engineering
Parallel Session
Cloud infrastructure for human beings

Speaker:

Data Platform Engineer
Allegro
Artificial Intelligence and Data Science
Parallel Session
Where data science meets software and ML engineering – a practical example

Speaker:

Associate Data Scientist
Philip Morris International

Speaker:

Lead Data Scientist Operations
Philip Morris International
Architecture Operations &Cloud
Parallel Session
ING Data Analytics Platform 3 years later. Lessons learned

Speaker:

Technical Lead for Data Analytics Platform
ING Hubs Poland

12.20 - 12.25

TECHNICAL BREAK

12.25 - 12.55

Data Engineering
Parallel Session
Auditing your data and answering the life long question, is it the end of the day yet?

Speaker:

Senior Data Engineer
Aidoc
Artificial Intelligence and Data Science
Parallel Session
Understanding Query Semantics at eBay

Speaker:

Staff Data Scientist
eBay Inc
Data Strategy and ROI
Parallel Session
Building a backbone of a data-driven enterprise: Big Delta Lake

Speaker:

Data Science Manager
Reckitt

12.55 - 13.00

TECHNICAL BREAK

13.00 - 13.30

Data Engineering
Parallel Session
10mln events per day from hearing aids to reports - a case study of bigdata analytics with Azure & more
Software Architect
Demant
Real-Time Streaming
Parallel Session
NetWorkS! project - real-time analytics that controls 50% of mobile network in Poland

Speaker:

Big Data Lead
GetInData

Speaker:

IT Operations Manager
NetWorkS!
Data Strategy and ROI
Parallel Session
Analytics Translator: The New Must-Have Role for Data-Driven Businesses

Speaker:

Associate professor Data Driven Business & People Analytic
University of Applied Sciences Utrecht

13.30 - 14.25

LUNCH BREAK

14.25 - 16.05

CASE STUDY

14.25 - 14.55

Data Engineering
Parallel Session
Scaling your data lake with Apache Iceberg

Speaker:

Senior Data Developer
Shopify
Architecture Operations &Cloud
Parallel Session
Developing and Operating a real-time data pipeline at Microsoft's scale - lessons from the last 7 years

Speaker:

Principal Software Engineering Manager
Microsoft
Artificial Intelligence and Data Science
Parallel Session
Eliminating Bias in the Deployment of AI and Machine Learning

Speaker:

Chief Technology Officer
Teradata Corporation

14.55 - 15.00

TECHNICAL BREAK

15.00 - 15.30

Data Strategy and ROI
Parallel Session
Digital Twins 101

Speaker:

AVP Technology
SoftServe
Real-Time Streaming
Parallel Session
TerrariumDB as a streaming database for real-time analytics

Speaker:

Co-Founder and CTO
Synerise
Artificial Intelligence and Data Science
Parallel Session
Feed your model with Feast Feature Store

Speaker:

Solutions Architect
Bank Millennium

15.30 - 15.35

TECHNICAL BREAK

15.35 - 16.05

Data Engineering
Parallel Session
Let your analysts build data pipelines on Modern Data Platform using SQL, DBT and the framework developed by GetInData

Speaker:

Software/Data Engineer
GetInData
Real-Time Streaming
Parallel Session
Cloud Native Stateful Stream Processing with Apache Flink

Speaker:

Lead Software Engineer
Ververica
Architecture Operations &Cloud
Parallel Session
COVID-19 is a cloud security catalyst

Speaker:

Group Head of Cloud Delivery
Endava

16.05 - 16.30

BREAK

PEER2PEER SHARING

16.30 - 17.30

ROUNDTABLES (ONLINE or ONSITE)

Parallel roundtables discussions are the part of the conference that engage all participants. It has few purposes. First of all, participants have the opportunity to exchange their opinions and experiences about specific issue that is important to that group. Secondly, participants can meet and talk with the leader/host of the roundtable discussion – they are selected professionals with a vast knowledge and experience.

There will be roundtable sessions, hence every conference participants can take part in 2 discussions, one each day of the conference.

 

 

Roundtable discussion
1. The unexpected journey to data cleansing

The data we use is often unstructured and varied. Conducting a simple analysis could become a burden: Where is the data I need? How do I make sure it’s accurate? Why are my queries taking so long? Designing the correct solutions to answer these questions in the optimal way could be painfully challenging, with very few success stories along the way. In this discussion we will share different approaches and solutions for data normalization. We'll meet people who've experienced different issues and hear how they tackled them.

Moderator:

Software Engineer
Neuralight
Roundtable discussion
2. Super-charge your Pandas code with Apache Spark

 Pandas is a fast and powerful open-source data analysis and manipulation framework written in Python. Apache Spark is an open-source unified analytics engine for distributed large-scale data processing. Both are widely adopted in the data engineering and data science communities. Even though there’s a great value in combining them in terms of productivity, scalability, and performance, it’s often overlooked. Join us for a live discussion, where you will hear and share your experience with combining Spark and Pandas to benefit from both worlds! We welcome all levels of expertise, from intermediate to advanced.

Moderator:

Senior Solutions Architect
Databricks

Moderator:

Senior Solutions Architect
Databricks
Roundtable discussion
3. Vector databases and vector search engines

Vector databases store data with vector embeddings, which are computed with Machine Learning models. Indexed vector embeddings enable fast similarity search and retrieval. An open-source vector search engine like Weaviate can be used to do semantic search, similarity search of text, images and other types of unstructured data, one-shot labeling, etc. These features of vector search engines enables you to scale ML models, build recommendation systems or do anomaly detection.

In this discussion we will talk about vector databases. You can learn about vector search engines, share your experiences, get updates from the latest techniques, meet people working in a similar field and get feedback on your ideas. Whether you're new to vector databases or identify as an experienced user, all are welcome to join!

Moderator:

Community Solution Engineer
SeMI
Roundtable discussion
4. CI/CD good practices for data pipelines

Moderator:

Manager of Data Analytics & BI
TrueBlue
Roundtable discussion
5. Data Governance in Modern Organizations

Traditionally, data governance has been defined as managing data integrity and the access of enterprise systems. Usually it consists of a centralized team with a steering committee, data stewards, process workflows and policies. In a traditional environment when you have a centralized data team, this can work well, but in today’s world where each department has their own analysts creating different analyses, such a project will likely fail. We'll discuss how today's organizations are approaching data governance given the fast-changing, decentralized environment of data today.

Moderator:

Founder & CEO
Select Star
Roundtable discussion
6. Dashboarding Nightmares: What most people forget to scope

Organizations are disappointed on the return on investment of their dashboarding efforts. At the same time, trends like natural language querying, data catalogs, and metric stores are arising. Are dashboards dead or maybe we haven't seen their best days yet.

Moderator:

Analytics Engineer
GoDataDriven
Roundtable discussion
7. From Data Lakes to Data Mesh - applying software architecture paradigms to data

Moderator:

Head of Product Engineering
Revolut
Roundtable discussion
8. AI act - do we need to regulate AI? When and how to do this?

Moderator:

Founder
MI2.AI
Roundtable discussion
9. Being an efficient data scientist. What skills, tools, and mindset are needed to become a data master

Moderator:

Senior Data Scientist
GetInData

17.30 - 17.35

SUMMARY & PRIZE GIVEAWAY

CEO & Meeting Designer
Evention
CEO and Co-founder
GetInData

18.00 - 22.00

EVENING NETWORKING SESSION | on-site, WARSAW

Let's get together! To talk, to meet new people, to see old colleagues. We invite you for a face 2 face interaction onsite.
More information HERE

28.04.2022 - 2ND CONFERENCE DAY| ONLINE

 

9.30 - 12.00

PARALLEL WORKSHOPS (ONLINE)

Data Vault on BigQuery

 

DESCRIPTION:

SESSION LEADER:

Customer Engineer
Google Cloud Poland

Data SCE at Professional Services Organization
Google Cloud Poland

What is a Data Quality Fabric and what’s in it for you?

 

DESCRIPTION:

SESSION LEADER:

Managing Consultant
Ataccama

Deep Dive into Data Science with Snowflake

 

DESCRIPTION:

SESSION LEADER:

Principal Sales Engineer, Data Science
Snowflake

12.00 - 13.00

BREAK

13.00 - 13.10

OPENING

13.10 - 13.35

KEYNOTE PRESENTATION

Artificial Intelligence and Data Science
Plenary Session
Benefits of a homemade ML Platform

Speaker:

Software developer
GetInData

 

Data Science Lead @ Search
Truecaller

13.40 - 14.10

PARALLEL SESSIONS

DATA ENGINEERING
Parallel Session
The Lakehouse - a new architecture to unify your data warehousing and AI use cases

Speaker:

Solution Architect
Databricks
Architecture Operations & Cloud
Parallel Session
Fine-Tuning Kubernetes Clusters for Data Analytics

Speaker:

Cloud Lead
Mindbox
Architecture Operations & Cloud
Parallel Session
Rise up and reach the cloud - evolution of a modern global healthcare data warehouse

Speaker:

Senior Technical Architect
IQVIA

14.15 - 14.45

CASE STUDY

DATA ENGINEERING
Parallel Session
Simplifying Data Architectures with Snowflake’s Snowpark

Speaker:

Principal Data Platform Architect, Field CTO Office
Snowflake
Real-Time Streaming
Parallel Session
Ingesting trillions of events per day with Apache Spark

Speaker:

Software engineer
Crowdstrike
Architecture Operations & Cloud
Parallel Session
Data Quality on Data Lakehouse: Implementation at Point72

Speaker:

Data Platform Associate
Point72

PEER2PEER SHARING

14.45 - 15.40

ROUNDTABLES (ONLINE)

Parallel roundtables discussions are the part of the conference that engage all participants. It has few purposes. First of all, participants have the opportunity to exchange their opinions and experiences about specific issue that is important to that group. Secondly, participants can meet and talk with the leader/host of the roundtable discussion – they are selected professionals with a vast knowledge and experience.

There will be roundtable sessions, hence every conference participants can take part in 2 discussions, one each day of the conference.

 

Roundtable discussion
1. Hadoop is legacy. Does the future belong to cloud data warehouses and delta lakes?

Moderator:

Director, IT Architecture, Real World & Analytics Solutions
IQVIA
Roundtable discussion
2. The Data Lakehouse – just another buzzword? Or a concept you can really use?

Moderator:

Solution Engineer
Vertica
Roundtable discussion
3. CloudOps: Specialization or standardization?

Moderator:

Chief Technology Officer
3Soft
Roundtable discussion
4. Engineers to engineers - Everything you always wanted to know about Big Data at Microsoft

Are you curious about how engineer’s life at Microsoft looks like? Would you like to know how our engineering teams work, learn, and collaborate effectively? Interested in how we build our services and solutions for Big Data workloads? If you answered YES to any of the questions, this round table is for you. Join our hosts from engineering teams at this “ask me anything” session.

Moderator:

Principal Software Engineering Manager
Microsoft

 

Senior Program Manager
Microsoft

 

Group Product Manager – Azure Engineering
Microsoft
Roundtable discussion
5. CI and CD in Data Science projects

Moderator:

Senior Data Scientist
GetInData

15.40 - 16.45

CASE STUDY

15.40 - 16.10

Data Strategy and ROI
Parallel Session
Implementation of BigData Platform in Digital vs Analog Financial company - case study.

Speaker:

Head of Architecture, Data and Infrastructure
W1TTY
Artificial Intelligence and Data Science
Parallel Session
Digging the online gold - interpretable ML models for online advertising optimization

Speaker:

Data Scientist
Ringier Axel Springer Polska
Architecture Operations &Cloud
Parallel Session
Managing Microsoft Azure at a leading capital markets fintech

Speaker:

Chief Cloud Engineer
Saxo Bank

16.15 - 16.45

DATA ENGINEERING
VOD
Analytical cubes in the service of data analysis

Speaker:

Engineering Manager for the Data Team
OLX Group
Artificial Intelligence and Data Science
Parallel Session
Learning From Experiments Without A/B Testing - Case Study From Willa (Swedish FinTech)

Speaker:

Data Scientist
Willa

Speaker:

Director of Data Science
Willa
Architecture Operations &Cloud
Parallel Session
Lessons Learned from Containerizing Data Infrastructure at Uber

Speaker:

Sr Software Engineer II
Uber

16.50 - 17.20

Parallel Session
How to accelerate your data-driven journey with an analytics framework?

What is a framework? How can the framework help you achieve a faster start? How can working with frameworks help you achieve long-term speed and agility?

#AnalyticsFramework #BusinessValue #EndToEnd #Scaling

Speaker:

Director of data & advanced analytics
ICA Gruppen

17.20 - 17.30

SUMMARY & CLOSING

CEO & Meeting Designer
Evention
CEO and Co-founder
GetInData

ONLINE EXPO + KNOWLEDGE ZONE

Free participation

We have great set of presentation available in the CONTENT ZONE that would be available pre-recorded as Video on Demand for conference participants in advance

VOD
How to keep the Data Lake clean instead of ending up with the Data Swamp using Data Layers a.k.a Bronze / Silver / Gold

Speaker:

CEO and Co-founder
Datumo
VOD
Deduplication and entity resolution with Zingg: open source tool using Spark and ML?

Speaker:

Founder
Zingg
VOD
Introduce Azure into your environment

Speaker:

VOD
Microservice Data Lakehouse

Speaker:

Chief Architect
Point72

Speaker:

Tribe Technical Lead
T-Mobile PL
VOD
See what’s underground via Machine Learning eyes (powered by cloud solutions)

Speaker:

Junior Data Scientist
SGPR.TECH

Speaker:

Senior Data Scientist
SGPR.TECH

VOD
AdTech Big Data in 10 minutes

Speaker:

Big Data Group Director
Adform
VOD
How Incorta Direct Data Platform can change your business

Speaker:

Head of Presales and Professional Services
MDSap
VOD
Implementing AI Strategy. You should know – ML is not enough

Speaker:

Centre of Expertise - AI
ING Bank Śląski
VOD
Implementing Augmented Analytics Platform

Speaker:

Advanced Data Analytics Competence Center Manager
ASTEK Polska

VOD
Data Preparation for Machine Learning

Speaker:

Field Consultant
Ab Initio
VOD
Ataccama ONE Platform

Speaker:

Managing Consultant
Ataccama

BIG DATA TECHNOLOGY
WARSAW SUMMIT 2022

April 26th-28th, 2022
Let's go virtual!

ORGANIZER

Evention sp. z o.o
Rondo ONZ 1 Str,
Warsaw, Poland
www.evention.pl

CONTACT

Weronika Warpas
m: +48 570 611 811
e: weronika.warpas@evention.pl

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