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Private and Open Data in Asia: A Regional Guide.
PechaKucha, now in over 800 cities, was devised in Tokyo in February 2003 as an event for young designers to meet, network, and show their work in public. PechaKucha is open to all Strata + Hadoop World conference attendees and will be held Tuesday evening, 5:00pm – 6:30pm, December 1, with a reception to start, and presentations beginning at 5:30pm. This will be held at the Suntec Convention Center, following the day’s sessions.
We’re interested in any topic as long as it’s interesting, from technology to culture to business to philosophy. The night includes time to network and chat, so be sure to bring business cards! We’re always looking for new speakers, but are not interested in product demos. Instead, present a how-to, a travelogue, something inspirational, lessons learned, or a forecast. Speakers are limited to 20 slides, which automatically advance after 20 seconds – that’s the fun of PechaKucha!
How is tech changing music? Entirely.
Nearly every facet of music production and consumption is being rethought in the face of data. Connected listeners, machine learning, and deep understanding of how and where music is consumed are changing the industry forever.
Over the course of 6 months and 70 interviews, Strata co-chair Alistair Croll dug into the burgeoning field of music science. Here’s what he learned, in 20 slides or less.
Learning the practice of listening
We all think we can do it naturally if we just focus or care enough. The reality is that like everything else, we need to build a practice around listening to innovate, change, grow, and learn. I’ll share my tips to help you nurture your nature in listening.
Social-Enabled Policing and Big Data
Criminals and terrorists are leveraging the sharing economy and social networking to achieve their illicit ends too! Police and law enforcement have to revive the spirit of community policing introduced in the 19th century: “the Police are the Public and the Public are the Police”. In this age of social networking, we call it “Social-Enabled Policing”; and Big Data has a big role in enabling it.
Hadoop – Disaster Recipies
With rapidly changing and evolving technologies in the “Big Data” domain, its is very important to focus on the use of “right” technologies for the “right” job and @ the “right” time.
If you miss anyone of the “rights” above it is likely that you may miss the bus.
I would begin with sharing real life failure experiences with few most popular technologies and conclude with a small brief about making a decision about choosing the “right” technology.
The skills to be successful in data
We hear lots of talk in organisations about the need for more analytics and this often manifests itself in investments in technology and technical training. Most organisations fail to focus on the softer skills that make data professionals successful in the world of organisational prioritisation, change management, stakeholder engagement and company politics. Our people need the skills to allow them to stand out in their organisation, to have a voice, to tell powerful and compelling data stories and to genuinely make a difference.
Achieving meaningful impact in R&D: This is my way
In this talk, I will share my experience and lessons learned, from my professional career in the industrial R&D, on how to achieve meaningful impact as a researcher (or engineer, scientist, technician, innovator, ). I will highlight the importance of sense of judgment and constant balancing act: that there is a time and place for viewing everything-is-a-nail vs no-one-size-fits-all. I will also touch on the phenomena of old-fashion-making-a-comeback that is prevalent in the industry. Throughout my talk, I will draw examples from my current team, in particular our approach to innovation life cycle and some of our team dynamics.
Get out of your developer’s way
You can’t forge a new path with an old map. Instead of using old methods as a way to keep pace with competitors, imagine the art of the possible. Ask yourself: What can we do now that we couldn’t do before? That’s how great organizations dominate their markets in times of significant disruption. Thanks to changes in big data technology and user behavior, what we can do now is perform experiments that deliver stark evidence about which actions will impact key business outcomes. That evidence helps us make the right decisions for the business and blow away the competition. But getting to that evidence requires analytics to keep pace with application development, and for both to iterate far faster than the months-long cycles we’re seeing today. Extending the agile DevOps model to big data enables that rapid innovation. Data-driven applications deliver the business outcomes we’re looking for, while at the same time, generate new data, creating a self-feeding environment in which data is continually curated, enriched, and increasing in value – in turn feeding new experiments and analysis. Forge your new path and get out of your Developer’s way.
There is no privacy in mobile data
“Our most personal device ever” is Tim Cook’s catch phrase about the Apple Watch. Indeed, the watch monitors not only our movements (with its gyroscope), but also our blood circulation.
Smartphones, mobile devices and other gadgets of the Internet of Things generate and collect up to millions of data points for one person per day. Although we are used to think of people as “average”, more or less doing the same things all the time, the data proves that the opposite is true: People act very distinctly, no two persons are alike – and hence the data collected on mobile devices is more unique than our fingerprints. But we don’t merely track ourselves – our mobile devices also accidentally harvest the data traces of others just passing by.
We’ll present how the data is generated in mobile devices, how to interpret the measurements, and demonstrate the impossibility of turning these data private again.
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