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.
Industry 4.0 and IoT Stage
On the Industry 4.0 and IoT 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.
As in the 2019 edition, we are continuing with the two-day setup. To accommodate the 2000 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).
Six Stages
This edition will again focus on data-first and AI-ready practical technical and business case studies. The program has 6 stages: Applied Analytics Data Science and AI; Analytics and Visualisation; Data Engineering; Data Management; Industry 4.0 and IoT; Machine and Deep Learning. All presentation are still 18 minutes with 10 minutes changing time between sessions. This will give the speakers an opportunity to directly dive into the topic and focus on the key learning points and for the delegates enough time to move from one stage to another. All presentations are held in English.
Data Clinic Area
Too often delegates want to meet the speakers after their presentations and ask questions. For this purpose, we are building the Clinic Area. A semi unconference model area with round table sitting where you can not only meet the speakers after their presentation and exchange experience, but also take part in the round table discussions organised by other delegates and partners. The program is partially set by us, and partially organised by the delegates.
Six Workshop Rooms
To provide a deeper insight into specific topics, on request by the delegates, as last year we will have six workshop (crash-course) rooms, each dedicated to a unique domain area: data-driven strategy, analytics & visualisation, machine learning, IOT analytics & Data Management, Data Management and Data Engineering. The Crash-Courses are 100 minutes each and limited to maximum of 40 participants. Although free of charge, the places are on first-come first-served basis and require pre-booking. Once the room capacity is reached, a waiting list will be open. The room capacity is indicated in the agenda, web page and the event app.
Data Octagon
Live streamed program providing insights into current data practices, trends, challenges and opportunities, as well as give overview of the latest technological breakthroughs, and glimpse into the future of data management, analytics and automation. The program consists of 30 to 45-minute panels and 20 minutes Tech News and it will be streamed live online on Hyperight Youtube and Twitter channel.
Networking Area
Over and over again delegates are asking for more networking time. On this edition we are introducing new features that will increase the opportunity for you to meet and network with the delegates. We will start the conference with a 30 minute speed networking session and time to explore the venue set up. You will also have the opportunity to meet the exhibitors, find a coffee buddy, enjoy a night out with your peers and new contacts, and have a coffee with them the day after.
Expo Area
In the expo area you will have the opportunity to meet local and global data management, analytics and automation software, hardware and service provider. A time in the program is dedicated for live demos and presentation on the exhibitor booths.
In-Person and Online
The event is both physical and virtual which means that you can either choose to either attend the summit in person, or you can follow the event and network with the delegates from the comfort of your work or home.
Which stage fits you best?
Explore the interactive expo map and discover what’s where on the event
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.
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.
What our PdMA experts say about the future of predictive maintenance
In the past month, we’ve talked to our PdMA experts who will be presenting at the Maintenance Analytics Summit 2020 and asked them to share their views on topics related to their presentation topics, current developments in the data- and AI-driven maintenance, but also on their outlooks on what the future holds for predictive maintenance.
Behind the scenes of detecting anomalies with deep learning at Airbus
As one highly interdependable and optimised industry, one minor anomaly in the airline industry may cause tremendous consequences. This is why detecting anomalies is beneficial not only for aircraft manufacturers but also for airlines and passengers.
What to consider when implementing an HR dashboard
As everyone working with HR becomes aware of the importance of data analytics and its impact on enhancing recruiting, workforce management and performance, it’s a matter of time when the question of an HR dashboard is put forward.
How data analytics is redefining the metal cutting industry
The manufacturing industry has been undergoing a dynamic shift towards digitalisation. Advancing technology, sensors, connectivity and the ability to store vast amounts of data has encouraged manufacturing owner-operators to converge IT and OT and utilise machine data to gain useful insights.
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 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 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.
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
Dao Mi
How to Data-Ops at Netflix Studios
DAY 1 M3 | Data Engineering Stage
16:30 - 16:50
Melisa Kleen
Business analytics playbook for fast growth companies
DAY 1 M2 | Analytics and Visualisation Stage
12:00 - 12:20
Ritesh Agrawal
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 M2 | Analytics and Visualisation Stage
10:30 - 10:50
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
Shreyansh Daftry
TBC | AI in Space: How NASA Uses AI and Machine Learning for Space Exploration
DAY 2 M8 | Machine and Deep Learning Stage
13:30 - 13:50
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 | Industry 4.0 and IoT Stage
10:30 - 10:50
Simon Moritz
Digital Infrastructure and AI paving the way for 4IR
DAY 1 M6 | Industry 4.0 and IoT Stage
16:30 - 16:50
Jukka-Pekka Salmenkaita
Applying AI in biomanufacturing
DAY 1 M6 | Industry 4.0 and IoT Stage
16:00 - 16:20
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
Frida Nellros
The 15+ year evolution of data driven product development of sustainable transport solutions
DAY 1 M6 | Industry 4.0 and IOT Stage
13:30 - 13:50
Gaurav Dixit
Leverage Testing to Understand Customers and Make Profitable Decisions
DAY 2 M1 | Applied Analytics Data Science and AI Stage
13:30 - 13:50
Iiris Lahti
Data Driven Design in Digital Media Services
DAY 2 M1 | Applied Analytics Data Science and AI Stage
12:00 - 12:20
Soeren Linau
Head of Swiss Cross Domain and LHG AI Studio
DAY 2 M6 | Applied Analytics Data Science and AI Stage
11:00 - 11:20
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