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14th & 15th of March 2019 • Kistamässan • Stockholm
Data Innovation Summit
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100+
speakers

on stage

54
exhibitors

in the expo area

24
workshops

during the event

2000+
participants

on site





Interactive Floor Map

DATA INNOVATION SUMMIT 2019

The shortest way to discover what´s happening 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 & INNOVATION STAGE

On the IOT Analytics and Innovation 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.

Speaker Companies 2019

Full schedule

Data Innovation Summit is constructed so it equally addresses all the elements of data-driven and AI-ready business: data, people, processes, technology. The event is built to be both business and technical, practical and inspirational, realistic and futuristic, educational and exciting, regional and global, live and digital, general and niched, inspiring and influential. It is showcasing some of the best data driven innovative projects, products, business ideas and technologies, presented by some of the most advanced and innovative organisations in the world.

Explore the agenda and build you own agenda based on topics and sessions you would like to attend across all stages and crash-course workshop rooms.


Speakers 2019
EDUCATE - ENGAGE - EXCITE - EMPOWER


HenrikGothberg_DIS2019.jpg
Henrik Göthberg
Director Group Financial Systems

VATTENFALL

Katie Bauer
Katie Bauer
Senior Data Scientist

Reddit

Bhairav-Mehta---Apple_Data_Innovation_Summit_2018
Bhairav Mehta
Data Science Manager

Apple

Aleksandr-Chuklin---Google-Zurich
Aleksandr Chuklin
Engineer / Researcher

Google Zürich

Francisca-Zanoguera---Expedia
Francisca Zanoguera
Senior Director Analytics

Expedia

Herve-Schnegg---Telegraph
Herve Schnegg
Principal Data Scientist

The Telegraph

Claire-Sullivan---Github
Claire Sullivan
Data Scientist - Machine Learning

GitHub

Susan-Wegner---Deutsche-Telekom
Susan Wegner
CDO

Deutsche Telekom

Ahmed-Khamassi---Statoil.jpg
Ahmed Khamassi
VP Data Science

Equinor

Dor-Kedem---ING
Dor Kedem
Lead Data Scientist

ING

Kai-Chaza---Ericsson
Kai Chaza
Director of AI

Ericsson

Adriano-Di-Toppa---Kemin-Industries
Adriano Di Toppa
IT Specialist

Kemin Industries

George-Buckbee Metso
George Buckbee
Head of Performance

Metso

Bertram-Pamminger Daimler-AG
Bertram Pamminger
Manager Data Products BOM & DMU

Daimler AG

Nikhil Simha
Nikhil Simha
Software Engineer, Machine Learning Infrastructure

Airbnb

Belen-Bandiera---Continental-AG
Belen Bandiera
Sr Data Scientist

Continental AG

Ritesh Agrawal
Ritesh Agrawal
Lead Data Scientist

Uber

Anando Sen
Anando Sen
Senior Product Manager

Uber

Adrian Badi
Adrian Badi
Senior Data Analyst

William Demant

Haakon Michael Austad
Haakon Michael Austad
Head of Customer Analytics

If Insurance

Mattias Fras
Mattias Fras
Head of AI Strategy & Acceleration

Nordea

Heikki_Pulkkinen
Heikki Pulkkinen
Data Scientist

VR Group

Eric Hasander
Eric Hasander
Director of Data Science

iZettle

Carl Xander Horn
Carl-Xander Horn
Data Science Manager

Klarna Bank AB

Co-Host Partner 2019


Partners 2019

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Media Partners 2019

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Whitepapers

3 building blocks of a Data Governance business case
Everyone knows that the world of data is changing faster than anyone anticipated. In fact, statistics show that 90% of the world’s data was created in the past 2 years.

Collibra Catalog


How to become a Data Governance Expert
You’ve been working with enterprise data for years. You’ve seen the good, the bad, and the downright ugly. And you’ve watched the business of data change. You’re already a data expert.

Governing your Data Lake: What every organization should know
Today, data is a differentiator. Organizations that can gather, manage, and use reports, dashboards, metrics, and models to create real value for their customers and stakeholders are thriving.

Enabling GDPR Compliance through Data Governance
On May 25, 2018, the General Data Protection Regulation (GDPR) goes into full effect. And according to Data Management Review, less than 15% of organizations feel they are very prepared to meet the data management requirements of the regulation.

Analytics: Dawn of the cognitive era
The rise of cognitive systems marks the birth of a new era. Cognitive capabilities take analytics to the next level, fundamentally changing how systems are built and interact with humans

Cognitive Manufacturing: An Overview and Four Applications that are Transforming Manufacturing Today
Cognitive manufacturing uses cognitive computing, the Industrial IoT, and advanced analytics to optimize manufacturing processes in ways that were not previously possible. It helps organizations improve fundamental business metrics such as productivity, product reliability, quality, safety and yield, while reducing downtime and lowering costs.

eBook: Build a True Data Lake with a Cloud Data Warehouse
This eBook helps you understand the full capacity of what a true data lake can deliver and the four pillars required to support it. The right data lake platform goes deeper and broader than ever before to reach unfathomable levels of new insight. A modern cloud data warehouse integrated with a modern data management solution and essential control and governance delivers a single source of truth that is secure, governed, and fast.

A 16 Step Data Governance Plan for GDPR Compliance
When GDPR takes effect in May 2018, data governance may become one of the most important elements of your data integration architecture. This white paper by data governance expert Sunil Soares provides a practical approach for implementing a strong data governance program that ensures that you have the policies, standards, and controls in place to enforce compliance.

Principles of Data Wrangling
Trifacta has released Principles of Data Wrangling: Practical Techniques for Data Preparation, the first how-to guide on data wrangling. But why should you read this book? It’s simple – because your time is as valuable as your data.

Six Core Data Wrangling Activities
Excel is a very powerful tool we all love, however it can be painful for data preparation. If you have to clean, standardize and combine disparate data together in a consistent view to accurately pilot your business, it can be very time consuming and prone to error.

Trifacta and DataRobot Solution for Machine Learning
Many organizations today look to technology to gain competitive advantages and improve their business. These organizations want to seize every opportunity and adopt a self-service approach to their operations, automate processes, optimize outcomes, and deliver impactful insights.

Data Onboarding: A Survivor’s Guide To Combining Unfamiliar, Disparate Data
Research shows 80% of analysts are spending their time manually preparing data instead of analyzing. By automating data prep processes, it will drastically improve the efficiency, timeliness and transformation into a more data driven culture.

Introducing the New Forrester Wave for Data Preparation Tools
According to Forrester, “Trifacta delivers a strong balance for self-service by analysts and business users.” Read The Forrester Wave™: Data Preparation Tools, Q1 2017 report and find out why Trifacta received the highest possible scores for Discover and blend, Standardize and enrich, Transform, Security and Governance, Sharing, and Deployment.

Reviews for Data Preparation Tools
Data preparation is an iterative-agile process for exploring, combining, cleaning and transforming raw data into curated datasets for self-service data integration, data science, data discovery, and BI/analytics.

How Deutsche Börse Wrangles Stock Exchange Data to Drive Product Development
See how Deutsche Börse leverages Trifacta’s data wrangling solution to transform a variety of data for new exchange market products. Deutsche Börse generates huge quantities of diverse data across its organization, and needed a platform capable of efficiently wrangling that data for downstream analytic use. Learn why Trifacta was the right choice.

How GSK Uses Data Wrangling for Clinical Trial Data to Accelerate Drug Development
See how GSK uses Trifacta’s Data Wrangling solutions to accelerate drug development by putting clinical trial data into the hands of the business user. GSK gets data from hundreds of sources and needs a solution that can standardize that data to provide insights.

Data Onboarding: Combining Disparate Data Into a Consistent View
In this Trifacta demo overview, watch the data preparation steps a CPG analyst goes through to combine retailer forecast data with the corresponding orders to identify forecast discrepancies.

Cloud BI: The Time Is Now
Data and applications are now being used as platform and software-as-a-service (SaaS) offers. Now is the time to start thinking about business intelligence and analytics in the cloud.

Drive Agile Business Decisions
Successful businesses understand that accuracy in planning is the foundation for smart and confident decisions in support of the business. But with increased competition and changing business models due to digital transformation, how can your business keep up?

Unleash the Killer API
When outspoken venture capitalist and Netscape co-founder Marc Andreessen wrote in The Wall Street Journal in 2011 that software is eating the world, he was only partly correct. In fact, business services based on software platforms are what’s eating the world.

Digital Trends That Will Shape Your Future [E-BOOK]
The future will be whatever we make it. Yet the future, so the saying goes, isn’t what it used to be. As digital technology rockets through an exponential growth curve, it is fundamentally changing how we live, work and play. Our traditional ways of thinking about the future are not enough.

How data gravity is pulling your analytics to the cloud
Data and applications used to be hosted locally, on organizations' own premises. But a cloud-computing revolution has changed this default. Data is moving to the cloud and data gravity is changing how software is run in organizations. Gartner says that more than $1 trillion in IT spending will be directly or indirectly affected by the shift to cloud during the next five years.

Redefining the role of IT in a modern BI world
Since its inception over two decades ago, the primary objective of business intelligence has been the creation of a top-down single source of truth from which organizations would centrally track KPIs and performance metrics with static reports and dashboards. This stemmed from the proliferation of data in spreadsheets and reporting silos throughout organizations, often yielding different and conflicting results.

Evaluation Guide: How to choose the right modern BI & analytics platform
This evaluation guide aims to support IT organizations as they evaluate and select a modern BI & analytics platform suitable for a broad, enterprise-wide deployment. The transition to a self-service-based, modern BI model requires IT to adopt a collaborative approach that includes the business in all aspects of the overall program (see Redefining the Role of IT in a Modern BI World).

Europe Data and Analytics Salary Guide 2017
The European salary guide from Harnham examines the hiring and remuneration trends for the data and analytics market across the region. From Germany to Gibraltar, we have your questions covered no matter where you are hiring or seeking a new role.

TDWI report: Why Your Next Data Warehouse Should Be in the Cloud
The Cloud model lowers the barriers to entry especially cost, complexity, and time-to-value that have traditionally limited the adoption and successful use of data warehousing technology.

6 Key Trends for IT Decision-Makers in 2017 and Beyond
Mhe Cloud model lowers the barriers to entry especially cost, complexity, and time-to-value that have traditionally limited the adoption and successful use of data warehousing technology.

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