Value Pack

Business Analytics Stage

Business Analytics (BA) Stage is one of the 5 stages you can attend during the third annual Data Innovation Summit 2018 in Stockholm. In this presentation you can explore the Business Analytics stage in detail, and learn why you and your team should attend the event and this stage. Once you have registered for the summit you can attend any of the five stages on the summit. Here we go!

Why attend

Business Analytics Stage

Strategy, Organisation and Implementation

The Glory days of Advanced Analytics are yet to come. As more and more organisations are using advanced analytics to gain competitive advantage or improve decision making process, it is no longer enough just to derive insight from data. Organisations need to be more data innovative and faster. Faster not only in getting that insight that will be the main differentiator, but also be fast in acting upon that insight, and to stay up to the latest technical trends and tools.

As Analytics has already proved to be a powerful tool for many department stakeholders, now it is time to spread the analytical capabilities throughout the organisation and make that data and insight available to everyone in the enterprise. But that is not an easy task.

Analytics operation model; the role of data and analytics in the company strategy and model; making data driven insight an integral part of business operations; quantifying lessons learned; lack of cross-department communication, and the most important, lack of senior management support and vision, are still the biggest challenges in the area. Data-driven innovation depends on the analytics function to lead the way.

On this years Business Analytics Stage, we will focus on strategy, organisation and implementation of Advanced Analytics. As the day will pass by, the presentations will dive into more in-depth topics and implementation examples. We are bringing practical case studies from leading organisations in the world. These presentations will bring insight on how to solve some of the challenges above, and present innovations in the area.

All presentations last 18 minutes + 2 min for quick Q&A.

What you will learn

  • From Information to Income: Monetizing Data In New Ways By Applying the Lessons of Digital Business - Timo Elliott, SAP
  • Bridging the Gap between BI and Operations - Ricardo Rodrigues, Opel
  • Enrich, Explore and Empower – Make the most out of Analytics, Fredrik Moeschlin, Findwise
  • Governed or Self-Service? Centralised or Distributed?
  • ableau at VMware: Enterprise insights through digitization and transformation - Kevin O’Callaghan, VMware
  • Metrics on the move — How Aldo Group puts live insight into the hands of users anywhere, anytime - David Dadoun, The Aldo Group
  • How Automated Machine Learning Accelerates Data Scientist Productivity -Hamel Husain, Airbnb
  • Just Like a DNA String: Videogame Player Segmentation through Frequent Sequence Mining - Alessandro Canossa, Sasha Makarovych, Massive Entertainment - a Ubisoft Studio
  • Data Prospecting to Production - Alun Jones, Konecranes Global Oy
  • Hottest Data Science Projects in the Heart of Silicon Valley - Mohammad Shokoohi-Yekta, Apple
  • Cognitive Analytics as a seedbed of innovation
  • How to utilize Advanced Analytics Engine to untangle organizations’ post-implementation glitches - Ahmed Elragal, Luleå University of Technology
Speakers are the ones who make events unforgettable, exciting and insightful.

Here are some of the awesome speakers on the Business Analytics Stage

Ricardo Rodrigues

Data Analytics Manager


Studied Telecommunications Engineering with a Master degree on Network Security. When doing IT audits, within the banking industry, realized the relevance of data analytics in supporting business decisions. Using the engineering mindset and analytical skills, decided to change career course and started doing statistical models for Credit and Market Risk and quickly realized this was my passion. Currently within the Automotive industry and supporting all business functions with business intelligence support, came to realize that every data point is like a piece of a puzzle and when you put all pieces together, you see the big picture. Seen as a person that seeks perfection, behaves as a person who is never satisfied with this achievements, dreams in being the person

David Dadoun

Director – Business Intelligence and Data Governance

The Aldo Group

David Dadoun is currently the Aldo Group´s Director of Business Intelligence and Data Governance. Prior to joining the Aldo Group he was the Director of a BI practice for the Keyrus Group. Over the last 15 years David Dadoun has advised a broad number of companies in the selection and implementation of BI tools, strategies, and roadmaps. He has managed BI projects including upgrades and migrations, and multiple BI platform deployments at small, medium, and Fortune 500 companies. David holds a Bachelor of Commerce in International Business from the John Molson School of Business and an executive Masters of Business Administration from ESG Montreal and Paris-Dauphine in France.

Hamel Husain

Senior Data Scientist


Hamel has over a decade of experience building data science teams and products from the ground up. During his tenure as a data scientist, Hamel has built world-class solutions for companies such as: Airbnb, DataRobot, SalesForce, AT&T, and MGM Resorts. Additionally, Hamel has led consulting engagements at for numerous companies in the retail, telecommunications, and restaurant industries at the consulting firms Accenture and AlixPartners.

Hamel's primary area of expertise is machine learning, and he has built a wide range of data products including: image classification, sales forecasting, churn prediction, customer lifetime value models and recommendation systems. In addition to his technical leadership, Hamel has built and led data science teams of up to 50 people..

Hamel currently serves as an advisor to several startups and is actively engaged as an organizer and speaker for the Open Data Science Conference. Furthermore, Hamel regularly volunteers in a Data Science capacity through DataKind for nonprofit organizations and charities. Hamel has attended The Georgia Institute of Technology, The University of Michigan, and Southern Methodist University where he obtained undergraduate and graduate degrees in the areas of mathematics, industrial engineering, computer science, and law. More information about Hamel can be found on his LinkedIn profile.

Alun Jones

Data Scientist

Konecranes Global Oy

Geographer by education, programmer by trade.Experience in education, retail, manufacturing, distribution and service industries. Worked for Konecranes since 1992 in a number of roles. Joined the Data 2 Knowledge cluster in January 2016 as Data Scientist.

Mohammad Shokoohi-Yekta

Senior Data Scientist


Mohammad is currently a Senior Data Scientist at Apple and a Lecturer at Stanford University. Prior to joining Apple, he worked for Samsung, Bosch, General Electric Research and UCLA on predictive modeling projects. He received a PhD in Computer Science from the University of California, Riverside and B.Sc. from University of Tehran. Mohammad is also the author of the book, "Applications of Mining Massive Time Series Data.”

Ahmed Elragal

Associate Professor of Information Systems

Luleå University of Technology

Prof. Ahmed Elragal (PhD, MBA, BSc) is an associate professor of information systems at Luleå University of Technology in Sweden. He has obtained his PhD from the University of Plymouth in the UK in 2001. Prof. Elragal has over fifty research papers and articles published at international conferences and journals, such as the Journal of Big Data, ECIS, AMCIS, and HICSS, etc. He is the winner of the 2010’s international case study competition on “Business Intelligence”, a prestigious international award. He has over 15 years of consulting experience, focused mainly on enterprise systems and business intelligence. He has helped different regional as well as multinationals organizations [including SAP, Teradata, Hyperone & Egypt Census Bureau] in the areas of enterprise systems, business intelligence, data mining, big data, analytics. In 2017, he has contributed to the formulation of Norrbotten’s Big Data Strategy.

Timo Elliott

VP, Global Innovation Evangelist


Timo Elliott is an innovation evangelist and international conference speaker who has presented the latest digital trends to business and IT audiences in over fifty countries around the world. He is a passionate advocate of digital transformation, analytics, and artificial intelligence, and his articles appear regularly in online publications such as Harvard Business Review, Forbes, ZDNet, The Guardian, and Digitalist Magazine. He has worked in the UK, Hong Kong, New Zealand, and the US, and currently lives in Paris, France. He has a first-class honors degree in Econometrics from Bristol University, UK, and holds a patent in the area of mobile analytics.

Alessandro Canossa

Game Data Analysts

Massive Entertainment - a Ubisoft Studio

Sasha Makarovych

Game Data Analysts

Massive Entertainment - a Ubisoft Studio

Before joining Massive Entertainment, Sasha did a Master of Finance program at Massachusetts Institute of Technology, where he focused on courses in predictive analytics and machine learning applications in various fields. Prior to that he have co-founded two start-ups in the video game industry, one of which was successfully acquired after breaking even. I also did several internships in the financial industry and agriculture, each with analytics focus.

Register Today

Prices from 2390 SEK

About the event

The Data Innovation Summit is an annual one day event in Stockholm bringing together the most innovative minds, enterprise practitioners, technology providers, start-ups and academics, working with Data Science, Big Data, Analytics, AI, IOT and Data Management. With over 60 Nordic and international speakers on five stages and plenty of learning and networking activities in the exhibition area, the 2018 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.

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