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

Schedule: IoT and its applications sessions

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11:1511:55 Wednesday, 1 May 2019
Mick Hollison (Cloudera)
Average rating: ***..
(3.33, 3 ratings)
Managing your data securely is difficult, as is choosing the right machine learning tools and managing models and applications in compliance with regulation and law. Mick Hollison covers the risks and the issues that matter most and explains how to address them with an enterprise data cloud and by embracing your data center and the public cloud in combination. Read more.
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14:0514:45 Wednesday, 1 May 2019
Data Engineering and Architecture
Location: Capital Suite 8/9
JIAN CHANG (Alibaba Group), Sanjian Chen (Alibaba Group)
Average rating: ***..
(3.33, 3 ratings)
Jian Chang and Sanjian Chen share the architecture design and many detailed technology innovations of Alibaba TSDB, a state-of-the-art database for IoT data management, and discuss lessons learned from years of development and continuous improvement. Read more.
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14:5515:35 Wednesday, 1 May 2019
Data Engineering and Architecture, Expo Hall, Streaming and IoT
Location: Expo Hall 2 (Capital Hall N24)
Geir Engdahl (Cognite), Daniel Bergqvist (Google)
Average rating: ****.
(4.00, 2 ratings)
Geir Engdahl and Daniel Bergqvist explain how Cognite is developing IIoT smart maintenance systems that can process 10M samples a second from thousands of sensors. You'll explore an architecture designed for high performance, robust streaming sensor data ingest, and cost-effective storage of large volumes of time series data as well as best practices learned along the way. Read more.
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12:0512:45 Thursday, 2 May 2019
Alasdair Allan (Babilim Light Industries)
Average rating: *****
(5.00, 4 ratings)
Alasdair Allan explains why the current age, where privacy is no longer "a social norm," may not long survive the coming of the internet of things, as new smart embedded hardware may cause the demise of large-scale data harvesting. Smart devices will process data at the edge, allowing us to extract insights from the data without storing potentially privacy- and GDPR-infringing data. Read more.
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14:0514:45 Thursday, 2 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 15/16
Christian Hidber (bSquare)
Average rating: ****.
(4.86, 7 ratings)
Reinforcement learning (RL) learns complex processes autonomously like walking, beating the world champion in Go, or flying a helicopter. No big datasets with the “right” answers are needed: the algorithms learn by experimenting. Christian Hidber shows how and why RL works and demonstrates how to apply it to an industrial hydraulics application with 7,000 clients in 42 countries. Read more.
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14:5515:35 Thursday, 2 May 2019
Data Engineering and Architecture
Location: Capital Suite 8/9
Jane McConnell (Teradata), Sun Maria Lehmann (Equinor)
Average rating: ***..
(3.67, 3 ratings)
In upstream oil and gas, a vast amount of the data requested for analytics projects is scientific data: physical measurements about the real world. Historically, this data has been managed library style, but a new system was needed to best provide this data. Sun Maria Lehmann and Jane McConnell share architectural best practices learned from their work with subsurface data. Read more.
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14:5515:35 Thursday, 2 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 15/16
Christopher Hooi (Land Transport Authority of Singapore)
Average rating: *****
(5.00, 3 ratings)
Christopher Hooi offers an overview of the Fusion Analytics for Public Transport Event Response (FASTER) system, a real-time advanced analytics solution for early warning of potential train incidents. FASTER uses engineering and commuter-centric IoT data sources to activate contingency plans at the earliest possible time and reduce impact to commuters. Read more.
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16:3517:15 Thursday, 2 May 2019
Data Science, Machine Learning & AI
Location: Capital Suite 15/16
Alexandre Hubert (Dataiku)
Average rating: *****
(5.00, 1 rating)
GRDF helps bring natural gas to nearly 11 million customers every day. Alexandre Hubert explains how, in partnership with GRDF, Dataiku worked to optimize the manual process of qualifying addresses to visit and ultimately save GRDF time and money. This solution was the culmination of a yearlong adventure in the land of maintenance experts, legacy IT systems, and Agile development. Read more.