From the 2014 Strata + Hadoop World conference in New York City, an interview with the Vice-President of Strategy at Silicon Valley Data Science about the Data Lake dream, the avatars of the space, and the parallel between Hadoop and Linux.
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Kenneth Cukier: Big data is better data
Kenneth Cukier looks at what’s next for machine learning — and human knowledge.
Self-driving cars were just the start. What’s the future of big data-driven technology and design?
Deep Learning: Intelligence from Big Data
Deep Learning begins to derive significant value from Big Data. It has already radically improved the computer’s ability to recognize speech and identify objects in images, two fundamental hallmarks of human intelligence.
Moderator
Steve Jurvetson, Partner, DFJ Ventures
Panelists
Adam Berenzweig, Co-founder and CTO, Clarifai
Naveen Rao, Co-founder and CEO, Nervana Systems
Elliot Turner, Founder and CEO, AlchemyAPI
Ilya Sutskever, Research Scientist, Google Brain
Kevin Slavin: The History and Future of Luck
In 2013, MIT’s Media Lab appointed Kevin Slavin to start and lead a new division of the lab called “Playful Systems”.
New York Times – Future Data Strategy
This internal New York Times innovation report reveals the future data strategy of the newspaper.
Traditional newspapers have to close. Even if these newspapers are producing great journalism they are failing in the art and science of getting their journalism to readers. They haven’t done enough to crack that code in the digital era.
The urgency of a digital first strategy is only growing because digital media is getting more crowded, better funded and far more innovative.
The New York Times envisions a strategy of growth, speed, agility and unlocking the power of data.
The focus of the digital first strategy of the New York Times is about getting more people to read more of the newspapers’s journalism.
This should also be achieved by using a “Data Strategy”.
The base for the strategy is the awareness to invest more in the unglamorous but essential work of tagging and structuring data.
The Times is hamstrung in theirs ability to allow readers to follow developing stories, discover nearby restaurants that the Times has reviewed or even has its photos show up on search engines.
Metadata is the key to understand and find the content in the Times archive. Tags that tie together articles, photos, and videos and geographic coordinates will structure the data to replace the current Times index. This should allow the ability to break up each article into atoms of news, such as facts, quotes, and statistics. To enable editors to quickly surface relevant content and context during breaking news.
The next step is to improve content personalization. Through the us of better algorithm based on the help of newsroom’s editors and analysis of readers reading patterns being planned by Design for NYT5 and the iPhone app.
From there the opportunity arise to track realtime data from users behavior on all media channels. The smart use of reader’s data is seen as essential to the future success to engage more readers . The Guardian, for example recently launched its “Known Strategy” with the newsroom leading the effort to improve how it collects, archives and uses reader data.
Inside the Times there is already a analytics groups which uses data to learn about their readers, changing habits as well as the effectiveness of their advertising and marketing. They also gather direct feedback from their readers about what they want from their apps and websites. This group translates those needs for Product and Design. But, data analytics should also be used for the newsroom to better understand reader behavior, adjust to trends and drive traffic to the Times journalism. Analytics skills are needed in many parts of the newsroom, including for top-level strategy as well as desk-level decision-making.
Looking on the New York Times Data Strategy from a data company’s perspective: The approach is still very people centric. There is a lac of understanding of the technology already available, to go beyond the limited vision shown in this report. If the New York Times is just focusing on the strategy displayed in this report they will even lose more ground to their competition. The focus should be “context”. Putting more than not just their archives and realtime data in relationships but furthermore the whole news ecosystem.
The New York Times is producing content since 1851, it is a “Data Company”. Therefore its should act as such
The Times want to hire analytics experts to work with news, platform, and product editors, newsroom strategists and the people trying to grow the Times audience.
Or hire Data Without Limits (DataWL)
NYT Innovation Report 2014
Dirk Slama (Bosch Software Innovations GmbH) : Industry 4.0 means batch size 1
NEXT14 – EMBRACE “THE NEW NORMAL”: Industry 4.0, Smart Factory, and Industrial Internet.
Cyber-physical-systems are the base for the industry 4.0
Viktor Mayer-Schönberger: Korrelationen sind gut genug für Big Data
re:publica 2014 – Viktor Mayer-Schönberge
Freiheit und Vorhersage: Über die ethischen Grenzen von Big Data – Big Data braucht Demut und Menschlichkeit.
Mayer-Schönberger stellt klar, dass Vorhersagen (predicitive analytics) durch Big Data selbstverständlich ein Risiko mindern und die Welt dadurch ein Stück weit einschätzbar wird. Doch es ist Vorsicht geboten wenn Vorhersagen drastische Konsequenzen haben können. Denn Vorhersagen sind nie perfekt, es sind nur Aussagen über eine Wahrscheinlichkeit. Aufgrund dessen darf nicht über Menschen gerichtet werden.
Auch und gerade deshalb fordert der Oxford-Professor das Recht auf Vergessenwerden im Internet sowie den Schutz menschlicher Handlungsfreiheit ein.
Kenneth Cukier, the key to Big Data is giving up trying to figure out the causality and just go with the correlation.
How problems are turned into big data problems and solved successfully with information. The key is to give up trying to figure out the causality and just go with the correlation.
Big Data an moral. What will we need to protect in a world of big data?
Maybe human volition, free will, responsibility.
“BIG DATA: A Revolution That Will Transform How We Live, Work, and Think,” is a revelatory exploration of the hottest trend in technology and the dramatic impact it will have on the economy, science, and society at large. Which paint color is most likely to tell you that a used car is in good shape? How can Con Edison catch the most dangerous New York City manholes before they explode? And how did YOU (well, Google) predict the spread of the H1N1 flu outbreak? The key to answering these questions, and many more, is big data, our newfound ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our newfound computing power to unearth revelations that we never could have seen before.
A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, especially the prospect of being penalized by for things we haven’t even done yet, based on big data’s ability to predict our future behavior.
Data Without Limits – Blog
Data Without Limits
DataWL is the reliable partner for fortune 500 companies, Government Agencies or Institutions.
If you think Data, think Data Without Limits your creative data agency.
We are a Creative Agency specialised on Data Analytics, Predictive Analytics and Data Visualization.
Big Data Analytics provides opportunities to discover deeper, more complete business insights through the analysis and visualization of significant volumes of rapidly changing structured and unstructured data.
Structured or unstrucred data, we love all kind of data. Our domain of experince spans from in car telemetric data, over social media data to realtime monitoring of video data. Each completed project makes us even more hungry, hungry for more data to push the limits of the possible even further. As a result we deliver insights to unleash the hidden power and value in your data sets.
Combining the competencies of data analytics, strategic consultancy and marketing. DataWL is able to offer a holistic approach to solve companies’ data challenges.
Industry 4.0
Industry 4.0 is the great opportunity to fuse Sensor Technologies, Data Analytics, Process Management and Automation to build a self-controling factory.
The economy is on the threshold of the fourth industrial revolution. Strong individualization, intelligent products and an extensive integration of customers and partners in the value creation processes are the characteristics of a company. The term “Industry 4.0” signifies those developments driven by IT innovations.
The Internet, mobile devices and smart objects are changing the face of manufacturing. It will have a profound effect on the way we make things. Hallmarks of this change will be the blanket use of information and communications technology as well as sensor systems. The real-time capability provided by mobile communication, autonomous objects and real-time sensor systems enables not just decentralized control but also ad hoc tailoring of processes. This in turn will help companies speed up and increase the flexibility of how they respond to customer requirements. Connected, intelligent products tell their user how they are to be best applied, new digital business models harness collected data offering additional services and as-a-service products, work pieces telling the shop floor machinery how they are to be processed, and all supported by a fully digital value chain. That is the core of Digital Industry 4.0 – referring to the 4th industrial revolution – highly intelligent cyber physical systems are connected to create the Internet of Things.
Prof. Dr. August-Wilhelm Scheer presented on the CeBIT Global Conferences his view of Industry 4.0
Prof. Dr. August-Wilhelm Scheer characterizes Industry 4.0 by a horizontal and vertical integration of production -systems and -resources. For him it is the consistent progression of the Computer Integrated Manufacturing (CIM) approach, described by the Y-CIM-Model, developed by him. With the implementation of integrated software systems for production planning and control (ERP Applications), the vertical integration was realized and thus extended from the scope of Supply Chain Management to a horizontal network with customers and suppliers across corporate boundaries. The Internet of Things, new technologies such as iBeacons and the latest developments in modern technologies (e.g. sensors, actuators) offer great possibilities to optimize processes, protect resources and to secure Germany as a production location.
Being a government initiative it is not about the buzzword which just appeared since February in media.
This graphic shows how often Industry 4.0 was mentioned in online media since January 1st 2014 untill March 31st 2014
But, the opportunity with Big Data and sensor technologies such as iBeacons to lower the investment cost in a significant way to optimize drastically existing manufacturing processes.
(Acatech • Industrie 4.0)
Industry 4.0 is a project in the high-tech strategy of the German government, which promotes the computerization of traditional industries such as manufacturing.The goal is the intelligent factory (Smart Factory), which is characterized by adaptability, resource efficiency and ergonomics as well as the integration of customers and business partners in business and value processes. Technological basis are cyber-physical systems and the Internet of Things. (From Wikipedia, the free encyclopedia)
