Future of the Digital Enterprise

What makes up the platform that will meet the needs of the mission-critical enterprise and help future proof the data-driven organization? Scott will discuss the critical requirements and how you can manage the lifecycle of all your data for analytics and operations using a new grid of processing and storage. The advantages are many and you will hear how this grid should include both cloud and on-prem to give you the complete view of your world.

Flattening the Cost of Curiosity

With the Internet of Things and technologies like Blockchain set to generate volumes of new data, the ability to process data into understanding is a growing challenge and one of the most disruptive business opportunities of our time. In the Insight Economy, companies that once bragged about their products will be bragging about their algorithms— competing based on how they turn data into insight, intelligence, and understanding at scale.

In IT, we’ve removed barriers to doing more with data through a number of fully appreciated phenomena, like the growth of open source. Enter a less appreciated phenomenon steadily moving into focus: infrastructure is going to matter, becoming a lift, shift, rift, or cliff when it comes to an organization’s ability to outpace the competition in the race to insights. The optimization of data movement in and out of accelerators like GPUs, for example— data-centric approaches to system design born in open server tech ecosystems— are massively raising the bar for what’s possible with data, while lowering barriers to innovation and adoption.

In this session, learn how we’re making it easier to become a data-driven disruptor.

Panel: Enterprise Adopters Q&A with Raj Verma, COO & President, Hortonworks

Industry leaders join to discuss how enterprises are driving business value and transformation with data. From securing sponsorship, driving deployment, and delivering measureable results, the panel will provide insight and advice from their data-driven journey.

Keith Renouard, DVP and Chief Enterprise Architect, Health Care Service Corp

YARN++ @ Microsoft

Microsoft operates multiple, datacenter-scale analytics clusters, each composed of tens of thousands of nodes processing millions of batch jobs daily. These clusters power analytics for teams across the company including Windows, Office365, Bing, and Skype, attracting diverse and challenging new workloads including streaming, interactive, and iterative computations. To meet these demands, Microsoft has embraced an open-source strategy that builds on Apache Hadoop YARN. Enhancing YARN to meet Microsoft’s needs has required innovation in core YARN components, integration with Microsoft infrastructure and processes, and deployment and stabilization at unprecedented scale.

In this talk, I will highlight salient milestones in this journey, including scaling YARN to datacenter-sized clusters, boosting utilization, and supporting predictable allocation SLOs. Our modifications have been contributed back to the Apache YARN code-base and many of these features already ship with current YARN releases. Our commitment is ongoing, and we will continue to contribute work in progress, such as evolving the YARN scheduler to better support long-running services.

When Data Becomes Strategy

Explore how data–mission critical in today’s business world–helps Walgreens Boots Alliance enable superior customer experience and helps people lead happier and healthier lives. Gain insights into a successful enterprise approach to data to drive actionable insights and improve value to customers and partners.

Precision medicine, machine learning

Enabling Precision Medicine with Healthcare Data Science Platforms

Shaping Data Platform to Create Lasting Value

With a long history of open innovation with Hadoop, Yahoo continues to invest in and expand the platform capabilities by pushing the boundaries of what the platform can accomplish for the entire organization. In the last 11 years (yes, it is that old!), the Hadoop platform has shown no signs of giving up or giving in. In this talk, we explore what makes the shared multi-tenant Hadoop platform so special at Yahoo.

Data in Motion Unleashed

Joe will show how you go from zero to live streaming in under 10 minutes, and you will also hear from an industry leader on real live applications.

The Value of Data

The importance of data has changed over the years. As the volume, variety and velocity of the data grew over the past few years, the economic value of data has been transformed by the big data phenomena that has enabled organizations to capture a broader, more granular and more real-time range of customer, product, operational and market interactions. Today, business leaders see data as a monetization opportunity, and their organizations are embracing data and analytics as the intellectual capital of the modern organization.


As users embrace Hadoop for analytics, it is becoming clear that an Enterprise-grade Hadoop Solution is needed for solving most deep analytic problems. This keynote will highlight HPE’s Hadoop framework for analytics that starts with understanding the business problem and ends with deployment and tuning of analytic models. HPE is using that as a basis to discuss how to best leverage “Hadoop and friends” throughout the process. This recommended approach is based on research and performance testing to allow the customer to extract immediate value from their data.

The 8 Second Data Rule

Our mobile device gives 24/7 access to news and information. So it’s no wonder the average attention span is 8 seconds or less. Yet most data available to brands today is often weeks or months old, meaning most of it is old news. So how can brands be confident that the data used to target audiences truly reflects who they are as consumers? Pinsight gets behind the lock screen to uncover a brand’s best customer, giving a predictive look at consumers to determine intent to engage. Kevin McGinnis, CEO of Pinsight, will share how his company taps into the power of mobile, analyzing vast volumes of demographic, behavioral and location data from the Sprint network, to fuel confident decisions that move businesses forward.

The Converging Worlds of Big Data and IoT: Why IoT will Fail to Deliver Value without the Context of Big Data

IoT has the potential to change the competitive landscape and drive transformation that leads to new business models. According to McKinsey, interoperability among IoT systems is key to capturing upward of 40% of the potential value. However much of the machine generated data collected today is not fully exploited or even used. Join Donna Prlich, CPO @ Pentaho, to hear about key industry trends and learn how big data provides the context for IoT to deliver measurable business value in organizations today.

Commoditizing Your Data to Sell – a Transportation Example

As with companies in nearly every industry, transportation enterprises are challenged to make good decisions quickly, providing competitive advantage through innovation and quality-of-service. Making these decisions requires intuition, information and agility; i.e., the ability to move in the right direction, right now. In many respects, this challenge is more difficult for the transportation industry than it is for many others. While there are certainly major players in transportation, MCMIS (Motor Carrier Management Information Systems) data suggests that 91% of all trucking companies operate fleets of 6 or fewer trucks, and 97% operate 20 or fewer. As a result of this extreme fragmentation, getting solid, timely information to serve as the basis for business decisions is very difficult for many companies. We will look at the way we can commoditize data for the small business to be as competitive as the big guys, like in pricing.

The Journey to Enterprise Artificial Intelligence

Artificial Intelligence has entered a renaissance thanks to rapid progress in domains as diverse as self-driving cars, intelligent assistants, and game play. Underlying this progress is Deep Learning – driven by the explosion of digital data, hardware advances, and breakthroughs in machine learning. We examine how AI is being applied in the enterprise for fraud detection and connected cars and discuss best practices to turn AI into real results.

Big Data in the not your father’s Enterprise

It’s finally happening. Big Data IS, REALLY, FINALLY going mainstream with full-on enterprise adoption. But guess what? That enterprise is not what it was just a few years ago. In the age of Digital, application automation is more critical than ever and Batch, that fundamental discipline everyone assumed was already dead, is front and center. Whether you look at Hortonworks and their work with NiFi and MiNiFi, AWS Batch, Steps, Glue, SWF and Data Pipeline, Azure Batch, Oozie, Azkaban, AirFlow, Luigi, Conductor, Hoodie and many others, managing data and processing pipelines is critical to extracting value from your Big Data “journey”. However, the Digital Enterprise has needs. It’s a hyper-heterogeneous, multi-faceted technology stack, dynamic infrastructure, developer-centric neighborhood that isn’t friendly to simplistic, single-use solutions. Doing Big Data right requires an orchestration solution that understands the Hadoop ecosystem and all your other technologies accumulated over the years, can deal with dynamic infrastructure and accommodate the needs of the creator class for high-speed application deployment.

Data Lake 3.0

Hear from Hortonworks founder Arun Murthy on what you can now do with Data Lakes 3.0, including building a containerized application with TensorFlow.

Data Capital In The 21st Century

Only a small fraction of global firms increase productivity year after year, according to the Organization of Economic Cooperation and Development (OECD). Creating and using unique stocks of data capital is one of the key tactics these firms use to widen their lead. Learn how two new ideas – data trade and data liquidity – can help all companies, not just superstars, take advantage of the data revolution. And hear examples of firms already putting these ideas into practice.

The Truth About Big Data

Hadoop Haters are going to hate…and they have.  Sometimes, they’ve gone as far as ignoring the key warnings that spotlight the Big Data Revolution.  In this rapid-fire session, Bruno Aziza, a Big Data veteran, shares some of the latest research in this space and review the “”5 Things You Should Know About Big Data in 2017”.  Hold on to your seat.  This session promises to contain controversy.  But, it will arm you with the information you need to combat the rants of today’s Big Data Distractors.

Can an Elephant Run Faster Than a Cheetah?

More and more businesses want to adopt the Agile methodology, embrace test-and-learn practices, and gain a competitive advantage with a data driven culture. Big Data & Cloud are becoming key drivers for business transformation. Learn how Liberty Mutual Benefits is using cloud automation and modern data technologies to achieve cheetah-like speed to market.