Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK

Schedule: Culture and organization sessions

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9:00–17:00 Tuesday, 30 April 2019
Data Case Studies
Location: Capital Suite 12
Paco Nathan (derwen.ai), Ganes Kesari (Gramener), Alicia Williams (Google), Semih Kumluk (Turkcell), Simon Moritz (Ericsson), Samuel Cristóbal (Innaxis), Volker Schnecke (Novo Nordisk), Julia Butter (Scout24), Cecilia Marchi (Jakala), Caroline Goulard (Dataveyes), Marc Rind (ADP), Juan Bengochea (Royal Caribbean Cruise Lines), Aaronpal Dhanda (EasyJet )
Hear practical insights from household brands and global companies: the challenges they tackled, approaches they took, and the benefits—and drawbacks—of their solutions. Read more.
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14:05–14:45 Wednesday, 1 May 2019
An Innovation Architecture industrializes AI from PoCs to production
Location: Capital Suite 12
Teresa Tung (Accenture), Jean-Luc Chatelain (Accenture)
Average rating: **...
(2.33, 6 ratings)
Innovation is abundant as companies reimagine themselves as data-driven and AI-powered businesses. How do enterprises organize to move beyond numerous, often similar proofs of concept (PoCs) into production-quality products and services? Teresa Tung and Jean-Luc Chatelain explore Accenture’s Innovation Architecture, which manages PoCs and pilots through embedding into scalable, saleable solutions. Read more.
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17:25–18:05 Wednesday, 1 May 2019
Creating a data engineering culture
Location: Capital Suite 17
Jesse Anderson (Big Data Institute)
Average rating: ****.
(4.71, 7 ratings)
In this talk, we will cover the most common reasons why data engineering teams fail and how to correct them. This will include ways to get your management to understand that data engineering is really complex and time consuming. It is not data warehousing with new names. Management needs to understand that you can’t compare a data engineering team to the web development team, for example. Read more.
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14:55–15:35 Thursday, 2 May 2019
Data-driven digital transformation and jobs: The new software hierarchy and ML
Location: Capital Suite 12
Secondary topics:  AI and machine learning in the enterprise
Robert Cohen (Economic Strategy Institute)
Average rating: **...
(2.00, 2 ratings)
Robert Cohen discusses the skills that employers are seeking from employees in digital jobs, linked to the new software hierarchy driving digital transformation. Robert describes this software hierarchy as one that ranges from DevOps, CI/CD, and microservices to Kubernetes and Istio. This hierarchy is used to define the jobs that are central to data-driven digital transformation. Read more.