Customer loyalty traditionally has been measured by running surveys to determine the customer's 'willingness to recommend', satisfaction, etc. Now, with the ability to analyze vast amounts of sales data, online behavior, and reading patterns, Barnes & Noble can measure shifts in customer loyalty at individual stores, regions, or channels. Methods that have long been available for measuring online behavior are now being applied to their brick-and-mortar stores, for a comprehensive view of customer purchase patterns, enabling Barnes & Noble to improve services that better address an individual customer's needs.

In November 2012, Barack Obama won a second term with the highest unemployment rate of any re-elected president in 76 years. How did he do it? The answer includes analytics and data from approximately two hundred million voters, donors and volunteers. Andrew Claster, Deputy Chief Analytics Officer for President Barack Obama’s 2012 re-election campaign, will discuss how analytics informed the Obama campaign’s fundraising, messaging, communications and voter contact strategies, and how the lessons learned can be applied to sales, marketing, recruitment, customer service and corporate communications.

Search is a massive big data problem and Bing is in it to be the best web search engine in the world. Ken Johnston shares information about the Bing big data platform and some of the techniques the team uses to continually improve search results across. He also shares how they manage GiGo for .

Presentation Details Coming Soon.

Presentation Details Coming Soon.

With the rise of Apache Hadoop, a next-generation enterprise data architecture is emerging that connects the systems powering business transactions and business intelligence. Hadoop is uniquely capable of storing, aggregating, and refining multi-structured data sources into formats that fuel new business insights. Organizations that embrace solution architectures focused on maximizing the value from ALL data will put themselves in a position to drive more business, enhance productivity, or discover new and lucrative business opportunities. Attend this session and hear Jeff Markham, Solution Engineer, Hortonworks discussing examples of Hadoop’s opportunity and the value it can unlock. Along the way he will discuss the kind of efforts required from the community, the solution ecosystem, and the enterprise in order to solidify Hadoop’s place within the enterprise.

Creating a brand entails knowing your customers: what they care about, how they interact online, and why they care about the content you provide. It is important to discover content that will connect with your audience that also supports your message. At bitly we know what specific content and topics users click on. We expand on basic notions of demographics to consider how subgroups of users have different affinities for various types of content. In this talk I will describe how we analyze audiences from bitly data and share incredible insights we have unearthed.

In a sales-driven business, a highly-accurate method of predicting sales units is critical, particularly as budget season approaches, financial expectations are released, and quotas are assigned. In this session, we will walk you through the process by which Paychex utilized predictive analytics to accurately predict future sales at the zip code level. The model output, coupled with 3rd party territory mapping software, has provided the sales organization with a robust tool to identify opportunities to “raise the bar,” thereby improving productivity, optimizing sales rep potential, and driving growth.

If your organization is like many, you’re capturing and sharing more data from more sources than ever before. As a result, you’re facing the challenge of managing high-volume and high-velocity data streams quickly and analytically. Planning a Big Data architecture is not about understanding just what is different. It’s also about how to integrate what’s new to what you already have – from database-and-BI infrastructure to IT tools, and end user applications. Oracle’s own product announcements in hardware, software, and new partnerships have been designed to change the economics around Big Data investments and the accessibility of solutions. In this session you will learn about Oracle’s Big Data Solution, and how it enables customers to expand their existing information architecture to provide a complete solution for acquiring, organizing, and analyzing ALL forms of large complex data.

For start-ups running at breakneck speed, who has the time to build up creative, proficiency, and governance in testing? Winners, of course. A culture of testing prevents inventories from going stale, gives marketers a goalpost by which to gauge comparative campaigns, and creates an environment where we must constantly question what we believe about customer behaviors. This session focuses on building the testing environment and on gaining insights from testing, because even loser test cells provide valuable customer preference data. Try your hand at guessing test winners from a sampler of real test examples illustrated, and take away practical tips from our learnings. “Adapt or perish, now as ever, is nature’s inexorable imperative” – H.G. Wells.

Most companies that are good at getting more value from their corporate data share several well-known practices, including significant investments in analytics talent and technologies, establishing centralized analytics units and using analytics to improve customer service. Companies that are great at wringing the most value from their data, however, approach their data very differently from other organizations. In this report, we reveal the distinctive practices of those companies that excel at deriving value from their data and draw lessons for how other companies can improve their performance with analytics.

Earlier this year, MIT Sloan Management Review, in partnership with SAS Institute Inc., surveyed 2500 individuals in 123 countries and 25 industries. Our analysis of quantitative data was supplemented with hour-long interviews that included conversations with senior leaders from organizations at the cutting edge of data analytics practice, including AstraZeneca, eBay, LinkedIn, Neiman Marcus, PayPal, PepsiCo and Team Great Britain, among others. From this research, we identified a group of companies that are relying on analytics to gain a competitive advantage and to innovate. This group – whom we are calling Analytical Innovators -- represents about 11% of our overall pool of survey respondents. They exist across industries and employ a variety of business models. They share several interesting characteristics: Analytical Innovators tend to view data as a core strategic asset; often have an urgent mandate to increase their use of analytics; and, have begun to use data and analytics to, in some cases, re-imagine their companies – not only in terms of what they do, but also in terms of what they can do.

Everyone wants fast access to Big Data to make good decisions as quickly as possible. The dropping price of memory is creating some exciting new opportunities in the areas of real time transaction processing and decision-making. Terracotta's BigMemory is an in-memory data management solution for the enterprise that stores “big” amounts of data in machine memory for ultra-fast access. This interactive presentation will focus on understanding your challenges and sharing how BigMemory has resolved similar challenges in different industries. Join us to learn about the in-memory revolution that is making the big data problem look small.

2012 saw the Big Data phenomenon gain great momentum and occupy front and center position as a focus area for serious investigation and investment across the Enterprise IT landscape.

Key questions in the minds of executives for 2013 and beyond include: What are the use-cases and patterns across industry/verticals ? How is economic value being created/extracted? What is the new/incremental value added? What are the challenges? How do the early adopters view the emerging technology landscape and lessons learnt?

Come hear from real practitioners leveraging Big Data Analytics in different domains to share their views around these themes.

Panel Speakers:

• Franklin Rios, President, Luminar, an Entravision Company
• Joshua Koran, Senior Vice President of Product Management, Turn
• Sujoe Bose, Senior Principal, Sabre Holdings
• Tom Ho, President, BISTel America

Exploding growth in the discovery of knowledge from Big Data is fueling the study of data through relationships that can be expressed as graph. In this presentation, Nilesh will introduce graph based data mining and structured machine learning techniques that creates new opportunities for monetization by extracting high value out of Big Data. At the same time large-scale graph processing creates new system-level challenges that require careful distributed systems design

With over 200 million people walking into stores each week, 43+ million unique visitors per month online, and access to the full twitter fire-hose (i.e. 200 million tweets per day), we at WalmartLabs are processing large amounts of data to help connect people to products and also provide unexpected insights to merchants. How do we turn this data into insights? How do we combine data internal to an enterprise with social data such as tweets and data from the "traditional" Web such as Wikipedia? When is social and web data useful? These are key questions when building any Big Data system. In this talk I will discuss our work in this area and give examples of where social and web data was used to solve some key challenges faced when building the eCommerce search engine of the world’s largest retailer.

A prominent storyline of the 2012 U.S. presidential campaign was that it was a "victory for the quants." In contrast to the traditional pundits who saw the race as neck and neck, quantitative data analysts used public opinion polls to predict with a high degree of certainty that President Obama would win reelection. How was this done? I describe the dynamic Bayesian forecasting model I used at votamatic.org to call the outcome of all fifty states, in June. Starting from a baseline historical prediction, the model tracked voter preferences and updated forecasts in real time from the large number of pre-election surveys released during the campaign.

In this talk, we will discuss how Etsy uses data to inform product development, from prioritization to experimentation to launch communication, and everything in between. At Etsy, we push code over 30 times a day and we have terabytes of data generated by the tens of millions of members of our community. This talk will cover the challenges of planning with continuous experimentation and deployment, as well as the evolution of Etsy's data culture.

Learn about how big data has driven product innovation at eBay. Andy Edmonds will counterpoint the utility of our large relational database system with Hadoop. A critical innovation has been creating intermediate shared aggregates in the Hadoop layer to enable many use cases, notably content specific insights.

Analyzing social media is one of the largest big data challenges businesses face today. On Twitter alone there are over 400 million new Tweets each day--totaling over 100 billion in the past couple years. Learn how Topsy created a platform that provides analysis of this data in milliseconds and how organizations are leveraging that information in their daily business.

In the next decade healthcare organizations will face a tsunami of data coming from both traditional and nontraditional sources. The challenge will be to turn data into usable information that enables healthcare providers to improve the quality of care, access and service, and affordability of care for healthcare consumers.

It's no secret that stellar Analysts are hard to come by these days... Or are they? It may be the case that we're just looking in the wrong places, or we're thinking about their roles incorrectly. Examining analyst work product at different stages in Yammer's extremely rapid growth has yielded deep insight into what it takes to be a good analyst, and what it takes to train one. This talk explores the ways in which we think about Big Data and the people we rely on to derive insight from it, including attracting talent, evaluating potential hires, and post-hire training.

Big Data are revolutionizing the way companies understand and interact with consumers. Steve Schwartz, Ph.D. and Danielle Giuseffi, MPH share how one start-up will transform data to create a hyper-personalized ecosystem for achieving health goals.

At LinkedIn, we have a business analytics team that work with all the functional teams for the business, from sales, product, marketing, to engineers. It has been really successful for the past 1.5 years since the team was built and we have delivered tremendous amount of incremental value to the business. In the presentation, I'll talk about how we work together with different teams to power the business from every angle.

At the San Diego Supercomputer Center (SDSC) at the University of California, San Diego we are leveraging SDSC's data-intensive expertise and resources in all aspects of big data. Gordon, a unique, data-intensive supercomputer recently introduced by SDSC, which currently ranks among the 50 fastest supercomputers in the world is a great platform for enabling significant advances and discoveries in the area of data-intensive research and predictive technologies in new environments.