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by Mathew Ingram and Elizabeth Charnock
We laud big data when it’s processing data types such as social media feeds, genome-sequencing data and server logs, but would the positive tone change if we were talking about monitoring your every digital interaction while at work to discover questionable behavior? Most people would but Cataphora CEO Elizabeth Charnock doesn’t agree, at least when it comes to the workplace. In fact, she thinks that in a world with increasingly larger corporations and distributed workforces, companies will be doing themselves and their employees big favors by keeping close tabs on what employees are doing.
by Ashlie Beringer and Derrick Harris
For the last 30 years we have been shifting from a society that places value on physical goods to a society that increasingly gains most of its value from invisible data. Data now has immeasurable value. As our sophistication in creating and storing the data increases so does that of those who want to steal it. This session will examine several facets of data security and provide a starting point for you to create your own big data security policy.
In no time, Hadoop has become the go to solution for big data and analytics. Hadoop and the emerging ecosystem of companies, solutions, and customer deployments have transformed this movement from early adopters to mainstream enterprise. We’ll explore what has changed from a product perspective, where the next crop of Hadoop-fosused startups are coming from, and what customers are doing today and in the near future. Be sure to join this comprehensive look a the Hadoop market.
Without Big Ideas, big data is a big back hole for industry. We bring you a curated selection of speakers and companies to present their shining new innovations to you.
by Damian Black
Applications are emerging that produce event stream data that is too voluminous to commit to database and process within the lifetime of the data. We need to rethink the way we can query and derive results. This talk presents an architecture that repurposes SQL into a massively parallel dataflow language that can process massive volumes of data in real-time with a latency of milliseconds.
by Om Malik and Mike Brown
Comscore has built is business on making sense of data. As it's marketplace has grown, so has the typical data set sizes it has to deal with, along with customers demanding quicker insights to make faster decisions. We talk to Comscore's founder and chief technologist about the future of decision-making technology evolving in a context where there is more data, less time and increasing compute power.
This session will trace how a combinatorial programming language developed by a team of MIT scientists to power NASA’s Mars Mission project has successfully been repurposed for an unlikely commercial use – digital advertising. Learn how the original inventor of this programming language applied “signals and systems” thinking to facilitate a digital advertising platform that uses scalable, intelligent machine-learning techniques for Big Data analytics and automated real-time decision making.
Everytime a consumer clicks, buys, checks in, or does anything they are creating a digital mark or impression somewhere. Each of these are happening at ever increasing rate, creating "digital signal streams." This panel examines the nature and importance of consumers "digital signals," the challenges inherent in processing them and the what key insights can be derived between the different streams. You'll hear examples of companies successfully inferencing from "Consumer Digital Signals" and what approaches can be taken to protect consumers from inadvertent breaches of their privacy.
There is vast potential for improved performance gains using applied predictive analytics, real time in many domains, and a need for systems that can "anticipate." The oncoming onslaught of sensor data in addition to the enterprise-generated content, all injected into the enterprise, provides abundant opportunities for new insights. For the advanced analytics and data mining practitioner, what differentiates is the consumption of analytics. Join us for a lively discussion on best practices, including industry examples of how you can use off-the-shelf components to stitch a system together, bolt on a few machine learning algorithms, and optimize.
We are moving to the next evolution of the consumer Web, the real-time web. As consumers demand a much more responsive and tactile experience with websites, the infrastructure powering these must also evolve. In this session, we look at Wordnik and how it has been able to shape its product proposition through utilizing technologies designed with responsiveness in mind. We also talk to them about the co-evolution of the real time web, real time big data streams and the NOSQL technologies needed to support these demands.
As DNA sequencing becomes increasingly affordable and accessible, the massive amount of genomics data represents opportunities to advance personal medicine. But how do you share a data set so incredibly big? In this talk we explore how a cloud data platform strategy will rapidly enable the sharing and analysis of the world’s DNA data with the innovators who need it most.
Traditional computational and storage methodologies don't scale easily or cost-effectively into the current generation of Big Data problems. Computational Storage is an alternative set of architectures that massively optimize solution design and construction. We'll explore several test cases in Genomics, Risk Analysis, Logistics and Satellite Imagery Analysis.
by insideHPC, Gary Grider and Garth Gibson
High performance computing has traditionally been the most demanding area of computing that pushed the edge of the envelope. In these circumstances a lot of pioneering work has been done that ultimately filter down to more pervasive and affordable applications. In this fireside chat we talk to a scientist from Los Alamos National Laboratories about how they reduce the time and cost of getting to critical insights by reducing the distance and the latency of compute memory. The conversation will look to successes in current deployments and what this signals for computer architectures for big data problems in the long-term.
Security at scale is harder than you’d think, especially when your big data platform is based on Infrastructure as a Service cloud computing. Join us for this introductory fireside chat as we discuss encryption for big data, how virtualization affects the security of big data, and emerging practices that will provide a big boost for Big Data security.
by Don Basile
Big data isn't just big, it's messy. CIOs are faced with the daunting task of unlocking the value of their data efficiently in the time frame required to make accurate decisions. This session will look at leading Fortune 500 companies who have leveraged solid state technology over mechanical disks to accelerate compute time.
The most successful complex technology of all time is the mobile phone. As everyone on the planet gets a phone, connects to a network and creates data, the deeper we sink into an ocean of data. This ocean of data represents a huge opportunity for those willing to submerge into its depth and fish for the insights. We talk to the most innovative new thought leaders in this space about how they are creating new values from the insights they generate and what is still left to explore in the uncharted depths of the mobile data ocean.
Find out how a company's data mining needs can inform its warehousing decision. While traditional warehousing solutions maintain their popularity, engineering-focused companies are starting to switch to Hadoop. Hear the pros and cons of both types of solutions, and address their respective strengths and weaknesses in terms of expense, operational management, scalability, extensibility, reporting, and security as discovered at the Data Discovery group at Eventbrite.
Doing data science at scale on Hadoop and HBase is difficult, and data about users presents unique challenges. In this talk you will learn why user-centric data is different from other types of large data, and how to leverage the right data layout to build an integrated analysis and serving platform. We will describe an architecture designed to perform these analyses (WiBiData), see real-world examples of user-centric data analysis solutions and talk about the potential future of user data analysis.
21st–22nd March 2012