2200
D E L E G A T E S
120
S E S S I O N S
74
E X H I B I T O R S
30
W O R K S H O P S

Join the biggest and the most influential Data and Advanced Analytics event in the Nordics!

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Towards Human Centered and Explainable Data and AI Innovation

Data is of vital importance for innovation and economic growth in the Digital and AI Economy. The purpose of data- and AI-driven innovation is to develop new or significantly improve existing human centred products, processes, methods or services. Data Innovation Summit is the leading data and advanced analytics event in the Nordics, constructed so it equally addresses all the elements of data-driven and AI-ready business: data, people, processes, technology and provides a holistic insight to the entire spectre of the data-to- insight-to-action process from data collection to visualisation and automation.

With over 120 Nordic and international speakers on six stages, six workshop stages and plenty of learning and networking activities in the exhibition area, the 2020 summit is the place to be for all professionals and organisations working with utilisation of data for increasing profit, reinventing business models, develop data-driven products, and increasing customer satisfaction.

Bringing you the hottest and most innovative data, analytics and AI case studies on these stages

Applied Analytics Data Science and AI Stage

The sessions are both business and technical, presenting a clear business output of data science, analytics, ML and AI to enhance customer experience, improve business process, reinvent business models and create new ones. Presentations by some of the most innovative companies in the world.

Analytics and Visualisation Stage

On this year’s Business Analytics Stage, we will focus on the latest methodologies of turning real-time data from multiple sources into insight, self-service BI, visualisation of data, prescriptive analytics, and much more. As the day passes by the presentations will dive into more in-depth topics and implementation examples.

Data Engineering Stage

Technical track focusing on agile approaches to designing, implementing and maintaining a distributed data architecture to support a wide range of tools and frameworks in production. Focus on Data-Ops, ML Ops, Auto ML, Cloud ML, Fast Data, data pipeline, data lineage, modeling, data flow monitoring, feature extraction and much more.

Data Management Stage

Technical and Strategy track focusing on best practices on leveraging data as an enterprise asset and ways of collecting and distributing quality data, while protecting privacy, usage restrictions and data integrity. This year’s focus is on the CDO agenda, data & information governance, Big Data quality, master data, warehousing, Data Lake, and much more.

IOT Analytics and Industry 4.0 Stage

On the IOT Analytics and Innovation Stage we will dive into how we can utilize IOT data to create insight and innovate through that data. We will start by looking at some innovative business examples, and then move to more technical examples on IOT data management, and utilization of advanced analytics, machine learning and blockchain.

Machine and Deep Learning Stage

Technical presentations on deploying Machine Learning, Deep Learning, Natural Language processing, Generative Adversarial Network and Artificial Intelligence in projects. Presentations by some of the leading experts, researchers and practitioners in the area.

BIGGER • EXTENDED • MORE INSIGHTFUL • GLOBAL

5th Anniversary
Celebrate Edition

Timo Elliott on
Data Innovation Summit 2018

What is new?

As in the 2019 edition, we are continuing with the two-day setup. To accommodate the 2200 delegates expected on this edition and still provide a great experience, we are utilizing the full capacity of the venue including the lower floor of the venue where this year’s workshops (crash course sessions) will take place. We are continuing with the same successful expo setup as last year that not only provides a natural movement flow between stages, but also accommodates the ambition of the conference to cover the entire spectrum of data innovation organisational and topic complexity. The agenda is yet again spread across two days, in a total of 6 stages plus plenum room, 6 new workshop rooms, new “Data after Dark” networking feature on the first day and new Clinic Room for deeper dive in conversations. More than 100 presentations, 30 workshops, 20 panels will take place during the event. As last year, the event is a hybrid with on-stage program and on-line live program streamed directly on our social media channels (Twitter & YouTube).

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Venue Map

Which stage fits you best? Explore the interactive expo map and discover what’s where on the event

Interarctive_floor_map_Data_innovation_summit_2018
M4 – DATA MANAGEMENT STAGE

Technical and Strategy track focusing on best practices on leveraging data as an enterprise asset and ways of collecting and distributing quality data, while protecting privacy, usage restrictions and data integrity. This year’s focus is on the CDO agenda, data & information governance, Big Data quality, master data, warehousing, Data Lake, and much more.

CRASH-COURSE SESSION ROOMS

On request by last years delegates, on this year’s edition we have set up several rooms for short workshops and crash-courses. The sessions are 100 minutes long and will provide training into various organisational, business, and technical topics. The rooms are limited to 40 people per crash-course session.

M6 – IOT ANALYTICS & INDUSTRY 4.0 STAGE

On the IOT Analytics and Industry 4.0 Stage we will dive into how we can utilise IOT data to create insight and innovate through that data. We will start by looking at some innovative business examples, and then move to more technical examples on IOT data management, and utilisation of advanced analytics, machine learning and blockchain.

M1 – APPLIED ANALYTICS DATA SCIENCE AND AI STAGE

The sessions are both business and technical, presenting a clear business output of data science, analytics, ML and AI to enhance customer experience, improve business process, reinvent business models and create new ones. Presentations by some of the most innovative companies in the world.

M2 – ANALYTICS AND VISUALISATION STAGE

On this years Business Analytics Stage, we will focus on the latest methodologies of turning real-time data from multiple sources into insight, selv-service BI, visualisation of data, prescriptive analytics, and much more. As the day passes by the presentations will dive into more in-depth topics and implementation examples.

M8 – MACHINE & DEEP LEARNING STAGE

Technical presentations on deploying Machine Learning, Deep Learning, Natural Language processing, Generative Adversarial Network – and Artificial Intelligence in projects. Presentations by some of the leading experts, researchers and practitioners in the area.

M3 – DATA ENGINEERING STAGE

Technical track focusing on agile approaches to designing, implementing and maintaining a distributed data architecture to support a wide range of tools and frameworks in production. Focus on Data-Ops, Fast Data, data pipeline, data lineage, modeling, data flow monitoring, feature extraction and much more.

P1 – KEYNOTES/ OPENING & CLOSING STAGE

The opening and the closing keynotes on this edition will take place in the expo area. A special stage is built to accommodate the number of del- egates and capture the emphasis of the keynote presentations. During the track sessions, the stage will be used for panel program consisted of speakers and experts. The panel program will be also streamed online.

D1 – DATA OCTAGON (online program)

Live streamed program providing in- sight into current data practices, trends, challenges and opportunities, as well as overview of the latest technological breakthroughs, and glimpse into the future of data management, analytics and automation. The program consists of 45-minute panels and will be streamed online on Hyperight youtube and twitter channel.

D1 – DATA OCTAGON (online program)

Live streamed program providing in- sight into current data practices, trends, challenges and opportunities, as well as overview of the latest technological breakthroughs, and glimpse into the future of data management, analytics and automation. The program consists of 45-minute panels and will be streamed online on Hyperight youtube and twitter channel.

C1 – DATA CLINIC AREA Unconference

An area with a semi unconference model with round table sitting where you can not only meet the speakers after their presentation and exchange experience, but also take part in round table discussions organised by other delegates and partners. The program is partially set by us, and partially organised by the delegates.

Meet the most innovative companies in the world

Anna Felländer on
Data Innovation Summit 2019

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Speaker Companies 2020

Get access to a cutting edge and premium content

Doug Cutting – Creator of Hadoop on
Data Innovation Summit 2019

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Short Schedule 2020

The quickest way to discover what and when is going to happen on the summit.
For more detailed information Request the Agenda or click Explore Sessions in Detail. 

7:30

Registration opens

8:00

Meet the Exhibitors

8:30

Speed Networking

9:00

Keynotes

10:00

Coffee and Networking

10:30

See more
Sessions

12:20

Networking Lunch

13:30

Sessions

15:30

Technology in Practice – Round 1

16:00

Sessions

17:30

Chairman’s Closing remarks

17:40

Networking Cocktail and Booth Crawl

19:00

Data after Dark

8:00

Registration opens

8:35

Chairman’s Opening remarks

8:50

Keynotes

10:00

Data Café – Find a coffee buddy

10:30

Technology in Practice – Round 2

11:00

Sessions

12:20

Networking Lunch

13:30

Sessions

15:00

Keynote

15:20

Chairman’s Closing remarks

15:30

Conference ends

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or

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Meet some of the biggest names in the industry

Errol Koolmeister on
Data Innovation Summit 2016

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Keynote Speakers 2020

Nick
Desbarats

Data Visualisation Evangelist
Practical Reporting

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Patrick van der Smagt

Head of AI Research
Volkswagen Group

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Speaker Lineup 2020

Henrik Göthberg

Founder
Dairdux

Robert Luciani

Founder & CTO
LakeTide

Nick Rockwell

Chief Technology Officer
The New York Times

Fabrizio Silvestri

Research Scientist
Facebook AI

Zheng Shao

Staff Data Scientist
LinkedIn

Emily Saliba

Data Scientist
Reddit

David Dadoun

Senior Director Data and Analytics Data Protection Officer
The ALDO Group

Virginia Dignum

Professor
Umea University

Ritesh Agarwal

Lead Data Scientist
Uber

Michal Gancarski

Data Engineer
Zalando

Juan Bernabe Moreno

Global Head of Advanced Analytics, AI and Data Lab
E.ON SE

Olivier Maugain

Corporate Analytics & Digital Technology Lead
Henkel

Dexter Fichuk

Data Scientist (NLP)
Shopify

Martijn Bauters

Head of Data Intelligence
Easyfairs International

Sébastien Foucaud

Chief Data Officer
HRS Group

Alessandro Canossa

Director of Data Research
Massive Entertainment – A Ubisoft Studio

Ahmad Azadvar

User Research Project Manager
Massive Entertainment – A Ubisoft Studio

Neil Hodgson

Capability Lead, Star Connect
Maersk

Simon Moritz

IoT Ecosystem Evangelist
Ericsson

Jukka-Pekka Salmenkaita

Director, AI & Machine Learning
Elisa

Arvind Keprate

Senior Engineer
DNV GL

Tejasvi Addagada

Deputy Vice President, Axis Bank Director of Board, IQ International
Axis Bank

Mattias Andersson

Partner / Senior Analyst
Miltton

Martin Dicksved

Partner / Senior Analyst
Miltton

Morten Bunes Gustavsen

Head of Data, DNB Wealth Management & Insurance
DNB

Mikhail Popov

Senior Scientist
RISE – Research Institutes of Sweden

Mats Adamczak

Data Scientist
Paf

Samar Singla

CEO & Founder
Jugnoo

Explore the entire speaker list

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An event you don’t want to miss!

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Showcase & Exhibit on Data Innovation Summit 2020

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Data Innovation Summit 2019

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Single Ticket

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2019 Gallery

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Handpicked Videos
from last edition

NLP for Online Conversations - Katie Bauer, Reddit
NLP for Online Conversations
– Katie Bauer, Reddit

As people live more of their lives online, there is a growing need for high quality natural language processing on social media posts, chat logs, and forum replies. Unfortunately, many common preprocessing routines do not capture information that is useful for conversational data. This talk will describe tools and techniques for addressing this unique type of language.

GitHub and Deep Learning on Graphs of Code - Clair Sullivan, GitHub
GitHub and Deep Learning on Graphs of Code
– Clair Sullivan, GitHub

GitHub is presently hosts approximately 0.5 PB of data on open source code. These data include the code itself and the various contributions to it, such as commits, pull requests, issues, comments, and users. A great deal of information can be learned about code and the open source community that creates it.

DataOps in Practice - Lars Albertsson, Mimeria
DataOps in Practice
– Lars Albertsson, Mimeria

DataOps is a methodology and culture shift that brings the successful combination of development and operations (DevOps) to data processing environments. It breaks down silos between developers, data scientists, and operators, resulting in lean data feature development processes with quick feedback. In this presentation, we will explain the methodology, and focus on practical aspects of DataOps.

Watch over 500 premium videos at

hyperight.com

TAKE ME TO THE VIDEOS

Henrik Göthberg

SUMMIT CHAIRMAN

DAY 1/2
P1 | Plenum

Robert Luciani

DATA OCTAGON | ONLINE PROGRAM LEADER

DAY 1/2
D1 | Data Octagon stage

Nick Rockwell

News in the Age of Algorithmic Recommendation

DAY 1
M1 | Applied Analytics Data Science and AI Stage

10:30 - 10:50

Fabrizio Silvestri

Misspelling Oblivious Embeddings

DAY 1
M8 | Machine and Deep Learning Stage

11:00 - 11:20

Zheng Shao

Leverage Testing to Understand Customers and Make Profitable Decisions

DAY 1
M2 | Analytics and Visualisation Stage

13:30 - 13:50

Emily Saliba

TBA

DAY 1
M4 | Data Management Stage

16:30 - 16:50

David Dadoun

TBA

DAY 1
M4 | Data Management Stage

16:00 - 16:20

Virginia Dignum

Responsible Artificial Intelligence

DAY 1
M1 | Applied Analytics Data Science and AI Stage

11:00 - 11:20

Ritesh Agarwal

TBA

DAY 1
M8 | Machine and Deep Learning Stage

16:00 - 16:20

Michal Gancarski

Serverless Data Infrastructure - A Complete Example

DAY 1
M3 | Data Engineering Stage

16:00 - 16:20

Juan Bernabe Moreno

Responsible AI for everyone

DAY 2
M1 | Applied Analytics Data Science and AI Stage

13:30 - 13:50

Olivier Maugain

Trend detection using social media data

DAY 1
M2 | Analytics and Visualisation Stage

16:30 - 16:50

Dexter Fichuk

Inheriting Bias in Models

DAY 1
M8 | Machine and Deep Learning Stage

16:30 - 16:50

Martijn Bauters

Why we pulled the plug out of a perfect working Machine Learning project

DAY 1
M1 | Applied Analytics Data Science and AI Stage

16:00 - 16:20

Sébastien Foucaud

How to scale Data function in a fast-growing Organization?

DAY 1
M1 | Applied Analytics Data Science and AI Stage

13:30 - 13:50

Alessandro Canossa

How Data Science and Machine Learning can help create better games

DAY 2
M8 | Machine and Deep Learning Stage

17:00 - 17:20

Ahmad Azadvar

How Data Science and Machine Learning can help create better games

DAY 2
M8 | Machine and Deep Learning Stage

17:00 - 17:20

Neil Hodgson

Star Connect IoT project

DAY 1
M6 | IOT Analytics and Industry 4.0 Stage

10:30 - 10:50

Simon Moritz

Digital Infrastructure and AI paving the way for 4IR

DAY 1
M6 | IOT Analytics and Industry 4.0 Stage

16:30 - 16:50

Jukka-Pekka Salmenkaita

Digital twins for complex manufacturing processes

DAY 1
M6 | IOT Analytics and Industry 4.0 Stage

16:00 - 16:20

Arvind Keprate

Bayesian Networks - A possible tool for Human Level Intelligence

DAY 2
M8 | Machine and Deep Learning Stage

13:30 - 13:50

Tejasvi Addagada

Data Democratization, Marketplace & Fabric for better Customer Management

DAY 2
M4 | Data Management Stage

13:30 - 13:50

Mattias Andersson

Applied, Automated and Artificial Intelligence

DAY 2
M1 | Applied Analytics Data Science and AI Stage

11:00 - 11:20

Martin Dicksved

Applied, Automated and Artificial Intelligence

DAY 2
M1 | Applied Analytics Data Science and AI Stage

11:00 - 11:20

Morten Bunes Gustavsen

From insight to action. Creating real value with data science in banking

DAY 1
M1 | Applied Analytics Data Science and AI Stage

17:00 - 17:20

Mikhail Popov

Drone and AI-assisted livestock monitoring

DAY 1
M1 | Applied Analytics Data Science and AI Stage

16:30 - 16:50

Mats Adamczak

Data quality is the shit

DAY 1
M4 | Data Management Stage

17:00 - 17:20

Samar Singla

How is IoT enabling the mobility and last-mile deliveries via drones

DAY 2
M6 | IOT Analytics and Industry 4.0 Stage

13:30 - 13:50