Quru attended the Data Innovation Summit in October 2021. The event provided two days full of information for data-driven and AI-ready businesses: data, people, processes and technology. Here are Quru’s top picks from the event, focusing on businesses we know well in Finland.
Caroline Carruthers – CEO, Carruthers and Jackson
In her keynote Caroline Carruthers gives insight on what Data Strategy actually is. It’s a term everyone is talking about it but what does it really mean, and how should benefit from it to create compelling vision and fight the fear of data.
She also shares examples on how to go from linear data strategy towards multi-dimensional strategy. She also explains how to balance Urgent Data Strategy, Immediate Data Strategy with the Target Data Strategy of the company. With these tips it will be easier to understand what to do now, how to handle legacy data and existing practices and how to keep the ultimate GOAL in mind.
Reading tip: Data Driven Business Transformation: How to Disrupt, Innovate and Stay Ahead of the Competition
Antti Myllymäki - Head of AI, OP Financial Group
In his presentation Antti Myllymäki from OP Financial Group shared insights on how OP Group found out that ambitious AI and DS goals are extremely hard to reach by building on top of full time Data Scientist roles only. They decided there was a need for Citizen Data Scientists, people who are not Data Scientsist by training but work with handling, analysing and sharing insights from data. Myllymäki shared best practises based on OP Group experiences.
This presentation also shares insights on how OP Group reorganized itself to work with AI by having more employees use, benefit, and get inspired by data.
5 steps to inspire Citizen Data Scientists:
Max Schultze, Data Engineering Manager, Zalando
Zalando’s Max Schultze shined light on what is a data mesh and how it can be used to set up a modern, distributed data management system for companies. Starting from the data analytics today, this introduction shared insights on what is the data mesh approach as an infrastructure platform, ranging from the companies just starting to promote a data mindset to those in the process of transforming their data infrastructure landscape, and the ones working for a sustainable data-driven future.
Schultze on what data mesh is:
Alberto Firpo - CEO and Co-Founder, Agile Lab & Tomas Dersjö – Senior Manager, Scania
Another good approach to data mesh (which seems to be today’s hot topic in data) was given by Alberto Firpo and Tomas Dersjö in their presentation how data mesh and the principles it's based on is such a good fit for Scania and its legacy.
From describing the friction in traditional “data organization” to data as a product and the ecosystem around it, and finally the data mesh building blocks - this speech explains how data mesh is utilized and how the world leading provider of transport solutions is practically implementing it.
Alberto Firpo’s hints in why to utilisize data mesh:
Daphne Cheung - Data Scientist, The Walt Disney Company
The introduction to storytelling with data at Disney was most probably one of the most expected keynote speeches within Quru’s data visualization team. In her speech, Daphne Cheung explained how to tell stories that span cultures, languages, and generations. She also gave practical steps to follow in developing your day-to-day data narratives.
Please note, no Disney case examples were used in this speech. However, her insights are still valid and give a good definition for using data as the story line.
Daphne Cheung’s 5 steps on how to turn data into a narrative:
Thomas Svahn - Vice President, Head of Insight & Data Sweden & Robert Engels - VP, Head of Data Science and Artificial Intelligence | Capgemini
Thomas Svahn and Robert Engels spread some Capgemini love and gave insights on how to use next generation, advanced analytics builds data-driven enterprises. They also showed examples on how visualisations play an important role in creating insights in humans, and whereas humans tend to focus on relations for understanding, many analytics methods analyse the facts.
Don’t miss Thomas Svahn’s examples on to integrate different datasets to provide fraud detection, how people use face paint to avoid face detection, and how fake dummy tanks were used in England during the second World War to make sure that the visualizations and reporting done in Germany were misleading.
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