Schedule: Business & Industry sessions

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Location: 120-121
Uwe Weiss (Blue Yonder)
Average rating: ****.
(4.00, 8 ratings)
While many companies are struggling to adopt big data and to unlock its potential, facing challenges of visualization and democratization of insight, a number of industry leaders are leapfrogging big data adoption and circumvent the analyst bottleneck by going straight to automation of core business processes. This requires overcoming a set of tough cultural, technical and scientific challenges. Read more.
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Location: 120-121
Melissa Santos (Big Cartel)
Average rating: ****.
(4.14, 21 ratings)
By having understandable abstractions for important data objects, Etsy has enabled employees across the whole company to actively take part in the collection and analysis of data. Converting data to objects allows us to more naturally convert analysis questions into code, and enforce business rules and definitions consistently. Read more.
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Location: 120-121
Aaron Frazer (Seeking Alpha)
Average rating: ****.
(4.40, 5 ratings)
Demonstrating how to use Google Docs for a flexible, extensible, self-service front-end for your data warehouse. A simple, cheap, stable, flexible, user-friendly alternative to traditional tools. Read more.
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Location: 120-121
Alistair Croll (Solve For Interesting)
Average rating: ****.
(4.58, 12 ratings)
In this session, Alistair Croll, author of the best-selling Lean Analytics and chair of O’Reilly Strata, will share what he’s learned in a year of working with and interviewing intrapreneurs all over the world. Read more.
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Location: 120-121
Roy Sasson (Outbrain)
Average rating: ****.
(4.27, 15 ratings)
Outbrain serves 150 billion content recommendations to more than 500 million monthly users. Data tells us what’s driving the mindset of the crowed. But how do you analyze if the individual user finds value in recommendations? Why being satisfied with click-focused-metrics is dangerous for growth? We outline a 3-layer framework for Data Scientists to analyze user engagement, facing such challenges. Read more.
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Location: 120-121
Kim Nilsson (Pivigo)
Average rating: ***..
(3.60, 10 ratings)
A data strategy is only as good as its execution. In the world of Data Science it has become increasingly apparent that business leaders focus on the technical aspects for success in data projects, when in fact the quality of the data team is key. I will in this talk share my experiences training data scientists, and give some key insights into how to build a high-performing Data Science team. Read more.
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Location: 116
Average rating: ***..
(3.75, 4 ratings)
We recently moved our entire data infrastructure to AWS: we now use Elastic MapReduce, Redshift and S3 for storage and processing. The talk describes the benefits and challenges of running in the cloud, how treating storage and processing as a utility allowed our small team to work on tools that democratized access to business analytics across the company and made us more happy in general. Read more.
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Location: 113
Daniel Waisberg (Google)
Average rating: **...
(2.82, 22 ratings)
In this presentation Daniel will discuss a process that can be used to go from data to stories. He will talk about ways to define the audience, create hypotheses, sketch data, analyze and build a story around it. The presentation includes the connecting dots game, Hulk, comics, architecture and other stories. Read more.
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Location: 113
Marcelo Soria-Rodriguez (BBVA Data & Analytics)
Average rating: ***..
(3.90, 10 ratings)
In this talk we will present practical cases on innovating with data in retail banking, a conservative industry. From initial idea to embracing open as a fundamental culture change, the talk will walk the audience through insights, lessons learned and practical examples on how to change the way value is delivered to customers. Read more.
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Location: 212
Amir Halfon (ScalingData)
This session will examine the challenges and opportunities associated with Big Data in a regulated environment, and the use of a new generation of data management technology to address them. Several case studies will be presented based on real-life production deployments. Read more.
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Location: 113
David Boyle (BBC Worldwide), Amanda Hill (BBC Worldwide), Dan Jabry (CrowdEmotion)
Average rating: ***..
(3.89, 9 ratings)
Emotions are messy and complicated. That meant we had to develop new data science and research methods to understand emotional engagement with out TV shows. But it also meant we had to be careful about how we brought that data to bear in a creative business like BBC Worldwide. Hear about how data science is making a big difference to how we build brands around the world. Read more.
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Location: 113
Average rating: ***..
(3.67, 3 ratings)
Everyone knows that creating value from big data requires the right skills, but what does this mean in practice? We present findings of a research project where we measure the skills needs of data-driven companies in 6 sectors, quantify the impact of data talent on company performance, and identify good practices to find, create value from and retain data talent. Read more.
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Location: 113
Carme Artigas (Synergic Partners)
Average rating: ****.
(4.80, 5 ratings)
Datafication is a new term used to describe the process of turning an existing business into a "data business".This is affecting many industry and services sectors.For this,data monetization strategies must be in place. New data sources(open data..) have a key role as well as the need to protect data privacy. Read more.