Sep 23–26, 2019

Data Case Studies

Tuesday, September 24, 2019 | Location: 1A 06

Data is changing every industry it touches. From retail to entertainment to logistics, collecting and analyzing work helps us improve it. A recent MIT study shows organizations that embrace data do 5-6% better a year in competitiveness and profitability—compounded, data is the difference between dominance and obscurity.

In this day-long series of case studies, we bring together a dozen examples of data in action across a wide range of companies and verticals. Get an inside look at the business models, infrastructure, and processes that leading companies have deployed. And hear hard-won lessons you can put to work immediately.

Tuesday, 09/24/2019

9:00am

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9:00am–9:05am Tuesday, 09/24/2019
Tutorial
Introduction to the Date Case Studies day-long tutorial. Read more.

9:05am

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9:05am–9:30am Tuesday, 09/24/2019
Rosaria Silipo (KNIME)
This is a review of AI case studies: from classic customer intelligence to IoT, from sentiment in social media to user graphs, from free text generation to fraud detection, and so on. The goal of this presentation is to inspire user creativity to apply AI in their own domain. Read more.

9:30am

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9:30am–10:00am Tuesday, 09/24/2019
Richard Evans (Statistics Canada)
Statistics Canada aims to be a key player in the Canadian AI ecosystem. Find out how Canada’s national statistical organization created and put in place its first AI/ML team, applying Lean Startup principles and a proactive hiring strategy to formulate a strategy that within months was delivering production-ready ML models in a complex and demanding data processing environment. Read more.

11:00am

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11:00am–11:30am Tuesday, 09/24/2019
Leah Xu (Spotify)
Spotify Wrapped is a year-in-music for active consumers and artists. Wrapped surfaces nostalgic insights derived from dozens of petabytes of user listening data. This talk sheds light on creating Wrapped for hundreds of millions of users in an ecosystem ingesting millions of events per second. Leah Xu discusses making engineering tradeoffs given demanding requirements and stringent deadlines. Read more.

11:30am

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11:30am–12:00pm Tuesday, 09/24/2019
Arup Nanda (Priceline)
Customer funnels are not unknown; but combining multiple data elements, business and systems, and charting our visitor drop-offs, along with A/B Testing has allowed Priceline to redefine the business, change product design and offer incentives to customers, on Cloudera, Airflow, Machine Learning with regression and classification models. Read more.

12:00pm

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12:00pm–12:30pm Tuesday, 09/24/2019
Predictive maintenance predicts the future of machines. Using data science we establish the machine’s unique life cycle and increase efficiency. In a world full of machines, we need to be the bridge connecting the methods of the past to the opportunities of the future. Read more.

2:00pm

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2:00pm–2:30pm Tuesday, 09/24/2019
Shreya Sharma (Expedia Inc.)
Over the last decade, logging of data has come a long way right from writing files in application logs to using sophisticated tools such as Splunk. As the data increased, it became harder to go through it manually and a system was needed to automate and standardized this telemetry data. Our talk shows how any company can leverage data to improve developer productivity and customer satisfaction. Read more.

2:30pm

2:30pm–3:00pm Tuesday, 09/24/2019 TBC

3:30pm

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3:30pm–4:00pm Tuesday, 09/24/2019
Martin Mendez-Costabel (Bayer Crop Science)
Cloud architecture is an extremely flexible environment for deploying solutions. Our recent learnings have revealed some interesting insights. One being that the first build of solutions, even using open source software, may quickly exceed initial cost estimates and could outpace ROI if not managed properly. The case study will focus on managing our Geospatial Platform and how we increased ROI. Read more.

4:00pm

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4:00pm–4:30pm Tuesday, 09/24/2019 Secondary topics:  Health and Medicine
Gloria Macia (Roche AG)
Healthcare is emerging as a prominent area for AI applications but innovators aiming to seize this chance face one major issue: achieving regulatory compliance. With a real industry case study, this talk will guide the audience through the current American & European regulatory framework for medical devices and provide a step-by-step guide to market for AI applications. Read more.

4:30pm

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4:30pm–5:00pm Tuesday, 09/24/2019
Gwen Campbell (Revibe Technologies, Inc)
It’s no surprise that our company needed to learn how to evolve to satiate the current data hungry market. Revibe launched its first hardware only device in 2015 and quickly learned that to stay alive, we needed to get our hands into data. We began the metamorphosis from a hardware company to a data company, and this presentation shows the transformation and lessons learned along the way. Read more.

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