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

Schedule: Sponsored sessions

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12:0512:45 Wednesday, 1 May 2019
Location: Capital Suite 4
Average rating: ****.
(4.60, 5 ratings)
Marcin Detyniecki offers an overview of the machine learning backend and its possible applications for the insurance business and other businesses based on the power of research merged with business. Read more.
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12:0512:45 Wednesday, 1 May 2019
Location: Capital Suite 2/3
Luca Piccolo (Data Reply), Michele Miraglia (Data Reply)
Average rating: ***..
(3.33, 3 ratings)
Retailers are facing a daunting challenge: remaining competitive in an ever-changing landscape that is becoming increasingly digital—which requires them to overcome rifts in internal systems and seamlessly leverage their data to generate business value. Luca Piccolo and Michele Miraglia outline Data Reply's approach, distilled while supporting retailers in successfully tackling these challenges. Read more.
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14:0514:45 Wednesday, 1 May 2019
Location: Capital Suite 2/3
Shant Hovsepian (Arcadia Data)
Average rating: ****.
(4.00, 4 ratings)
With cloud object storage, you may expect business intelligence (BI) applications to benefit from the scale of data and real-time analytics, but traditional BI in the cloud faces not-so-obvious challenges. Shant Hovsepian discusses considerations for service-oriented cloud design and shows how native cloud BI provides analytic depth, low cost, and high performance. Read more.
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14:0514:45 Wednesday, 1 May 2019
Location: Capital Suite 4
Joel Horwitz (WANdisco)
Joel Horwitz shares best practices WANdisco clients have taken to evolve their data architecture to become a LiveData company. Read more.
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14:5515:35 Wednesday, 1 May 2019
Location: Capital Suite 4
Damon Cortesi (Amazon Web Services)
Average rating: ****.
(4.71, 7 ratings)
Damon Cortesi demonstrates how to use AWS Glue and Amazon Athena to implement an end-to-end pipeline. Read more.
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14:5515:35 Wednesday, 1 May 2019
Location: Capital Suite 2/3
Larry Orimoloye (Dataiku)
Average rating: *....
(1.00, 1 rating)
Recommender systems are tools that provide suggestions that best suit the customers' needs, even when they're not aware of it. Larry Orimoloye explains how Dataiku helped one of the world's leading vacation retailers drive customers toward better recommendations. Read more.
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16:3517:15 Wednesday, 1 May 2019
Location: Capital Suite 2/3
Julio Lopez (Inditex)
Julio López explains how Zara Tech uses indirect observation and ML engineering to augment the understanding of Zara's processes in order to improve them. Join in to learn how Zara Tech built and uses a Spark ML pipeline to provide KPIs to improve the shopping experience. Read more.
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16:3517:15 Wednesday, 1 May 2019
Location: Capital Suite 4
Average rating: **...
(2.67, 6 ratings)
Deb Seys shares the results of a study that she oversaw at eBay in collaboration with the Kellogg School of Management at Northwestern University. Examining the work of 2,000 analysts and almost 80,000 queries, the study revealed that a data catalog can be used as a learning platform that increases analyst productivity and creates a more collaborative approach to discovery and innovation. Read more.
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17:2518:05 Wednesday, 1 May 2019
Location: Capital Suite 2/3
Luke Han (Kyligence)
Average rating: **...
(2.00, 1 rating)
Augmenting data management and analytics platforms with artificial intelligence and machine learning is game changing for analysts, engineers, and other users. It enables companies to optimize their storage, speed, and spending. Luke Han explains how the Kyligence platform is evolving to the next level, with augmented capabilities such as intelligent modeling, smart pushdowns, and more. Read more.
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11:1511:55 Thursday, 2 May 2019
Location: Capital Suite 2/3
Ben Lackey (Oracle)
Average rating: *****
(5.00, 1 rating)
Join Ben Lackey to learn how Oracle Cloud Infrastructure's architecture makes it the right place to run compute-intensive partner applications like H20.ai, Cloudera, DataStax, and more. Read more.