Presented By O'Reilly and Cloudera
Make Data Work
Sept 29–Oct 1, 2015 • New York, NY

Sponsored conference sessions

Wednesday, September 30

9:15am–9:25am Wednesday, 09/30/2015
Location: Javits North
Joseph Sirosh (Microsoft)
Average rating: ****.
(4.46, 85 ratings)
Join Microsoft’s Joseph Sirosh for a behind-the-scenes sneak peek into the creation of the viral phenomenon How-Old.net. He'll cover how it got to 50 million users in 7 days, the unexpected big data challenges that came with it, and the surprising learnings they had about people and systems. Read more.
9:25am–9:30am Wednesday, 09/30/2015
Location: Javits North
Ron Kasabian (Intel), Michael Draugelis (Penn Medicine)
Average rating: ***..
(3.63, 79 ratings)
Even in this era of intense medical breakthroughs, many illnesses still evade accurate and timely diagnosis. Clinicians' must often rely on static diagnostic guidelines, that result in late care and too many false alarms. Half of all heart failure patients can go undiagnosed. Read more.
9:30am–9:35am Wednesday, 09/30/2015
Location: Javits North
Tim Howes (ClearStory Data)
Average rating: ***..
(3.42, 67 ratings)
This keynote unveils why rapid modernization of BI is taking place, the business use cases driving it, and what’s essential in next-generation solutions. Read more.
9:35am–9:40am Wednesday, 09/30/2015
Location: Javits North
Jim McHugh (Cisco)
Average rating: ***..
(3.72, 61 ratings)
IoE, IoT, and big data – three topics you hear and read about often in our various industries. Let’s quickly look at these market and technology dynamics, and see how they are each in their own way ’democratizing’ data access and analysis, resulting in new businesses, technologies, and improved community solutions throughout the world. Read more.
11:20am–12:00pm Wednesday, 09/30/2015
Location: 1 E6 / 1 E7
Robert Novak (Cisco)
Average rating: ***..
(3.67, 3 ratings)
Big data has moved beyond the bleeding-edge, early-adopter stage. If you're not using it now, you will be soon. But big data deployments are not a cookie-cutter, one-size-fits-all effort. Cisco Big Data Consulting Systems Engineer Robert Novak will present real-world deployment stories and use cases for big data on Cisco UCS, especially (but not exclusively) around Hadoop environments. Read more.
11:20am–12:00pm Wednesday, 09/30/2015
Location: 1 E14
Matt Winkler (C+E) (Microsoft)
Average rating: ***..
(3.57, 7 ratings)
At Microsoft, we process exabytes of data to run our own businesses. Learn how you can process big data in the cloud at massive scale with no hardware to deploy, software to tune/configure, and infrastructure to manage. We’ll also talk about overcoming common obstacles in big data adoption such as a high learning curve, cost of implementation, tuning infrastructure, and providing security. Read more.
11:20am–12:00pm Wednesday, 09/30/2015
Location: 1 E15
Vin Sharma (Intel)
Average rating: ***..
(3.50, 2 ratings)
To accelerate enterprise deployment of big data analytics, Intel and partners introduced an open source trusted analytic platform-as-a-service for data scientists and app developers to build and deploy advanced analytics applications at cloud scale. Join us and discover how you can customize and develop your own big data solutions with this platform. Read more.
11:20am–12:00pm Wednesday, 09/30/2015
Location: 3D 06/07
Ali Tore (ClearStory Data)
Average rating: ***..
(3.20, 5 ratings)
In this session, you will learn why organizations are embarking on a mission to understand the “now” of their businesses, what they are doing with their internal and external data to drive continuous insights, and how their businesses benefit from these insights. Read more.
1:15pm–1:55pm Wednesday, 09/30/2015
Location: 1 E6 / 1 E7
Tags: iot
Sarah Aerni (Pivotal)
Average rating: ****.
(4.11, 9 ratings)
The promise of IoT is that it will forever change the way people and businesses interact with the world. Using illustrative use cases, Pivotal will demonstrate the fundamental concepts required to drive true impact from these connected devices. We will cover which models are most appropriate, what considerations around data access and processing are critical, and which tools available. Read more.
1:15pm–1:55pm Wednesday, 09/30/2015
Location: 1 E14
Moderated by:
Andrew Brust (Datameer)
Panelists:
Jeff Jarrell (American Airlines), Ryan Wright (Kelley Blue Book), Kendell Timmers
Average rating: **...
(2.91, 11 ratings)
Beyond the euphoria of what big data can do, and the stress that comes from feeling that you’re not doing enough, how can you really get started? What are some concrete things you can do and some reasonable results you can expect? This panel, featuring real customers who are technology implementation leaders, will help you answer these questions. Read more.
1:15pm–1:55pm Wednesday, 09/30/2015
Location: 1 E15
Anthony Dina (Dell)
Average rating: ***..
(3.50, 2 ratings)
The only guarantee in life is change. That’s exactly what makes the world interesting and innovative, and that’s exactly what the large internet properties are counting on: to disrupt traditional businesses with an always-on, data-centric business model. Read more.
1:15pm–1:55pm Wednesday, 09/30/2015
Location: 3D 06/07
Moderated by:
Robert Eve (Cisco)
Panelists:
Robert Novak (Cisco), Nenshad Bardoliwalla (Paxata)
Average rating: ***..
(3.33, 6 ratings)
As big data becomes a pervasive force in the enterprise, many of our fundamental ideas around how to optimize compute, storage, network, and resource management are being stretched. Read more.
2:05pm–2:45pm Wednesday, 09/30/2015
Location: 1 E6 / 1 E7
Eric Frenkiel (MemSQL), Noah Zucker (Novus Partners), Ian Hansen (Digital Ocean), Michael DePrizio (Akamai Technologies)
Average rating: **...
(2.25, 4 ratings)
In-memory is no longer just a trend: it’s an imperative, for high volume, real-time data workloads. With the relational, distributed MemSQL database, modern enterprises are unlocking value from gigabytes and terabytes of data. Learn about some of latest applications and deployments of in-memory technology from Akamai Technologies, Novus, and Digital Ocean. Read more.
2:05pm–2:45pm Wednesday, 09/30/2015
Location: 1 E14
Vishal Bamba (Transamerica), Murthy Mathiprakasam (Informatica)
Average rating: ****.
(4.25, 4 ratings)
In this session, learn how leading customers have built a unified big data fabric on top of Hadoop, using technologies like Informatica to repeatably deliver trusted data assets to a large community of data consumers, for a multi-dimensional view of customers. Read more.
2:05pm–2:45pm Wednesday, 09/30/2015
Location: 1 E15
Peter Schlampp (Platfora), Chris Kudelka (Riot Games)
Average rating: ***..
(3.67, 6 ratings)
League of Legends has more than 67 million players per month. The company needed an analytics solution that would work well with their push-model data pipeline. In this session, data engineer Chris Kudelka will discuss how their game designers use Riot's data pipeline and Platfora to measure and validate player-focused changes like improvements to game servers and client performance. Read more.
2:05pm–2:45pm Wednesday, 09/30/2015
Location: 3D 06/07
Robby Dick (BMC Software)
Average rating: ***..
(3.00, 5 ratings)
This session describes how organizations are managing Hadoop and big data workflows with an enterprise workflow solution that provides a graphical user interface for managing all the complex components of the enterprise application fabric. They gain SLA management, forecasting and change impact analysis, auditing, reporting, and self-service via mobile devices. Read more.
2:55pm–3:35pm Wednesday, 09/30/2015
Location: 1 E6 / 1 E7
Alex Loffler (TELUS)
Average rating: ****.
(4.00, 4 ratings)
Security teams study many months and years of data for baselining and incident forensics, but IT operations may only want to store weeks or months of data to analyze for operational insights. And the two different needs can be difficult to reconcile. Learn how TELUS's security analysts provide value to both teams. Read more.
2:55pm–3:35pm Wednesday, 09/30/2015
Location: 1 E14
Bill Porto (RedPoint Global)
Average rating: **...
(2.80, 10 ratings)
This session covers why continual, adaptive optimization is a key to success with real world machine learning models. Bill will detail the applicability of machine learning tools with the pros/cons of each. Learn how to optimize processes to drive more predictable outcomes from business decisions. Tools for automating access to changing data and removal of noise and error will also be reviewed. Read more.
2:55pm–3:35pm Wednesday, 09/30/2015
Location: 1 E15
Jonathan Gray (Cask)
Average rating: ****.
(4.25, 4 ratings)
Data lakes represent a new data architecture that provides enterprises with the scale and flexibility required for big data: unbounded storage for unbounded questions. While Hadoop is the de facto standard for implementing data lakes today, significant time and effort are still required. This talk introduces Cask Hydrator, a new open source data lake framework and drag-and-drop UI built on CDAP. Read more.
2:55pm–3:35pm Wednesday, 09/30/2015
Location: 3D 06/07
Sheetal Dolas (Hortonworks)
Businesses are moving from large-scale batch data analysis to large-scale real-time data analysis. Apache Storm has emerged as one of the most popular platforms for this purpose. This talk covers proven design patterns for real-time stream processing. They have been vetted in large-scale production deployments that process tens of billions of events/day and tens of terabytes of data/day. Read more.
4:35pm–5:15pm Wednesday, 09/30/2015
Location: 1 E6 / 1 E7
Matthew Derda (Pepsi), Douglas Stradley (Trifacta)
Average rating: ***..
(3.92, 13 ratings)
Pepsi analyst Matthew Derda and Trifacta Director Customer Success Doug Stradley discuss why data wrangling is critical to empowering analysts to efficiently access, and incorporate, diverse big data sources for organizational analysis. Get first-hand examples where traditional ETL and scripting approaches fall short, and why “self-service” approaches are critical to big data initiatives. Read more.
4:35pm–5:15pm Wednesday, 09/30/2015
Location: 1 E14
Jon Haddad (The Last Pickle)
Average rating: ***..
(3.00, 3 ratings)
Everyone knows that Python isn’t suitable for massive scale analytics, right? Wrong. Spark 1.3 introduced data frames, which allow for high performance Spark batch jobs, streaming, and machine learning over massive datasets. In this talk you’ll learn how to combine Cassandra, a highly scalable, always-on OLTP data store, with PySpark, a framework for distributed computation. Read more.
4:35pm–5:15pm Wednesday, 09/30/2015
Location: 1 E15
Alex Gorelik (Waterline Data), Jim Kaskade (Janrain), David Tabacco (Merck & Co., Inc.), David Paige (Cox Automotive)
Average rating: ****.
(4.20, 5 ratings)
This talk is about the best practices approach to accelerate data discovery while complying with security and data governance needs. Learn how to implement an automated and governed inventory of your data assets. Open up your data lake with secure self-service to find and understand data quickly. Read more.
4:35pm–5:15pm Wednesday, 09/30/2015
Location: 3D 06/07
Bruce Reading (VoltDB)
Average rating: **...
(2.33, 3 ratings)
You have 10 milliseconds. Less than the blink of an eye, the beat of a heart – that’s how much time you have to ingest fast streams of data, perform analytics on the streams, and take action. Ten milliseconds to win a customer, 10 milliseconds to make a sale, 10 milliseconds to save a life – it’s not much time. Read more.
5:25pm–6:05pm Wednesday, 09/30/2015
Location: 1 E6 / 1 E7
Anant Chintamaneni (BlueData)
Average rating: ****.
(4.29, 7 ratings)
Hadoop multi-tenancy is becoming a must-have – in order to accommodate multiple lines of business, multiple concurrent Hadoop jobs, multiple versions of Hadoop, multiple applications, security isolation, and more. This session will discuss these requirements and share recommendations on how to deploy a secure multi-tenant Hadoop environment with simplicity, agility, and low management overhead. Read more.
5:25pm–6:05pm Wednesday, 09/30/2015
Location: 1 E14
Bill Schmarzo (EMC Consulting)
Average rating: ****.
(4.20, 5 ratings)
Bill Schmarzo, EMC CTO of Global Services, and author of “Big Data: Understanding How Data Powers Big Business," will utilize a workshop approach to help you identify where and how to integrate data and analytics into your business strategies. Read more.
5:25pm–6:05pm Wednesday, 09/30/2015
Location: 1 E15
Samuel Cozannet (Canonical)
Average rating: ****.
(4.00, 2 ratings)
Whether you’re a large enterprise or a startup, successfully competing with modern, nimble, fast-moving companies like Uber or Airbnb can only be done with modern, model-driven development environments and big data solutions. Infrastructure shouldn’t restrict the interactions between relational data and big data. Development shouldn’t slow analytics. Read more.
5:25pm–6:05pm Wednesday, 09/30/2015
Location: 3D 06/07
Eric Brewer (Google)
Average rating: ****.
(4.00, 3 ratings)
In this talk, we will describe a Cloud-optimized deployment model for Spark and Hadoop, and explore how these tools and Cloud-native services complement each other to form the most productive and efficient data processing platform. Read more.

Thursday, October 1

9:20am–9:25am Thursday, 10/01/2015
Location: Javits North
Ben Werther (Platfora)
Average rating: ***..
(3.73, 45 ratings)
The traditional BI and analytics tools of the last decade have made it difficult for users to work directly with their data. With the latest innovations in big data discovery platforms, a new role has emerged: the citizen data scientist. In this keynote, Ben will share Platfora’s research behind the importance of this emerging role so that companies can become truly data-driven. Read more.
9:25am–9:30am Thursday, 10/01/2015
Location: Javits North
Paul Kent (SAS)
Average rating: ***..
(3.70, 40 ratings)
Imagine the possibilities of having all of your data in one place – at a reasonable cost – with the computing potential to learn from relationships between data in all domains. Advanced analytics and Hadoop are changing the way organizations approach big data. Hear tips from the future and learn about key patterns emerging from a wide cross section of Hadoop journeys. Read more.
9:45am–9:50am Thursday, 10/01/2015
Location: Javits North
Average rating: ***..
(3.60, 45 ratings)
IBM fellow and director, Watson Content Services, IBM Read more.
11:20am–12:00pm Thursday, 10/01/2015
Location: 1 E6 / 1 E7
Alexander Barclay (UnitedHealthcare Shared Services)
Average rating: ***..
(3.83, 6 ratings)
UnitedHealth Group has long been defined by our innovative approach to health care, and our approach to IT and analytics is no different. With the goal of making health care more affordable by identifying fraud, waste, and abuse activities, this session will provide details on how we leveraged Hadoop for payment integrity analytics to identify thousands of high-risk providers and claims. Read more.
11:20am–12:00pm Thursday, 10/01/2015
Location: 1 E14
Michele Goetz (Forrester Research), Chuck Yarbrough (Pentaho)
Forrester Research Principal Analyst Michele Goetz discusses findings from Delivering Governed Data for Analytics at Scale, a June 2015 commissioned study conducted by Forrester Consulting on behalf of Pentaho on the topic of data governance and delivery. Read more.
11:20am–12:00pm Thursday, 10/01/2015
Location: 1 E15
Paul Kent (SAS)
Average rating: ***..
(3.33, 3 ratings)
Imagine the possibilities of having all of your data in one place – at a reasonable cost – with the computing potential to learn from relationships between data in all domains. Advanced analytics and Hadoop are changing the way organizations approach big data.Hear tips from the future and learn about key patterns emerging from a wide cross section of Hadoop journeys. Perhaps they’ll inspire yours. Read more.
11:20am–12:00pm Thursday, 10/01/2015
Location: 3D 06/07
Average rating: **...
(2.00, 1 rating)
Financial institutions use data such as streaming news feeds and proprietary data for insight. One company is taking filings from 130 countries and data from 500,000 equity instruments to create real-time applications. Data integration is essential for information to be trusted in these applications. Explore an architecture designed to capture all data and ensure it is trusted. Read more.
1:15pm–1:55pm Thursday, 10/01/2015
Location: 1 E6 / 1 E7
Average rating: ***..
(3.50, 2 ratings)
If you’re struggling with determining which implementation of SQL on Hadoop can meet your analytics needs, you’re not alone. Join us for a discussion on how YP.com, a leading local marketing solutions provider in the U.S. dedicated to helping local businesses and communities grow, uses HP Vertica for SQL on Hadoop to solve their organization’s big data challenges. Read more.
1:15pm–1:55pm Thursday, 10/01/2015
Location: 1 E14
Emma McGrattan (Actian)
Average rating: ****.
(4.33, 6 ratings)
Can Hadoop now handle your enterprise analytic workloads? Actian SVP of Engineering Emma McGrattan will describe the various solutions that comprise the SQL on Hadoop landscape, identify the features that are important for those modernizing their enterprise analytic workloads on Hadoop, and describe the successes that Actian customers have had in moving their BI and Analytic workloads to Hadoop. Read more.
1:15pm–1:55pm Thursday, 10/01/2015
Location: 1 E15
Nidhi Aggarwal (Tamr, Inc.)
Average rating: ****.
(4.00, 2 ratings)
Enterprises find it far too costly and time-consuming to locate all of the data relevant to analysis. Data is so fragmented that most enterprises lack even a basic inventory of all sources and attributes -- an enormous constraint on getting return on your big data investment. Tamr Catalog solves this by creating an inventory of all enterprise metadata in a central, platform-neutral place. Read more.
1:15pm–1:55pm Thursday, 10/01/2015
Location: 3D 06/07
Jeff Pollock (Oracle), Chris Lynskey (Oracle)
Average rating: ****.
(4.00, 1 rating)
In this session you’ll learn how Oracle has leveraged Spark-based machine learning (ML), natural language processing (NLP), and data graph semantics (Linked Open Data) to create the simplest and most powerful big data discovery and big data preparation tools in the market. Read more.
2:05pm–2:45pm Thursday, 10/01/2015
Location: 1 E6 / 1 E7
Ron Bodkin (Google)
Average rating: ***..
(3.80, 5 ratings)
While schema on read is powerful, it’s just a first step on the journey to understanding effective ways of working with data in new big data systems. In this talk we highlight new patterns of working with data. Read more.
2:05pm–2:45pm Thursday, 10/01/2015
Location: 1 E14
Jagane Sundar (WANdisco)
Average rating: ***..
(3.50, 2 ratings)
This talk explores the actual behavior of eventual consistent systems aka mostly inconsistent systems, while presenting a paxos algorithm alternative. We’ll highlight the Amazon use case and various fixes made to S3 in order to enable Hadoop workflows, and alternatives offered by Cassandra, then explore Paxos as an alternative to such inconsistent systems for Hadoop Storage and HBase solutions. Read more.
2:05pm–2:45pm Thursday, 10/01/2015
Location: 1 E15
Nirmal Ranganathan (Rackspace)
Average rating: ***..
(3.40, 5 ratings)
All of us involved in big data are working to decrease time to insights. We're building Spark on Yarn clusters with Hadoop ecosystem components, and there are clear benefits to this implementation. However, there are other use cases that may benefit from a more streamlined stack. Read more.
2:05pm–2:45pm Thursday, 10/01/2015
Location: 3D 06/07
Charlie Crocker (Autodesk)
Average rating: ***..
(3.83, 6 ratings)
Building design software for industries from engineering to construction, manufacturing to media, meant Autodesk needed to architect its analytics platform to handle massive amounts of data. Learn how Autodesk uses open-source technologies like Kafka and Hadoop and integrates them with solutions like Splunk, Google BigQuery, and Tableau to achieve data insights at scale. Read more.
2:55pm–3:35pm Thursday, 10/01/2015
Location: 1 E6 / 1 E7
Reiner Kappenberger (HP Security Voltage)
Average rating: ***..
(3.67, 3 ratings)
Building a strategy and methodology that protects sensitive data is vital in securing your big data systems and enterprise assets. Learn how people protect big data in Hadoop, and understand how protecting the information is possible without removing the value of the data, or paying a performance penalty. Read more.
2:55pm–3:35pm Thursday, 10/01/2015
Location: 1 E14
Ashish Verma (Deloitte)
Average rating: ****.
(4.50, 8 ratings)
The Internet of Everything (IoT) continues to give rise to new business models in the Retail, Industrial Manufacturing, Healthcare, Insurance, Medical device manufacturers, Telecommunications, and Technology industries. Learn what those efforts are and how to capitalize on these opportunities for your clients. Read more.
2:55pm–3:35pm Thursday, 10/01/2015
Location: 1 E15
Matt Yanchyshyn (Amazon Web Services)
Average rating: ****.
(4.33, 9 ratings)
Want to get ramped up on how to use Amazon's big data web services and launch your first big data application on AWS? Read more.
2:55pm–3:35pm Thursday, 10/01/2015
Location: 3D 06/07
Phil Kim (Capital One Labs)
Average rating: ***..
(3.83, 6 ratings)
Capital One is on a mission to Change Banking for Good. Join Capital One as we take you through the journey of the Data Lab. How did we get started? What have we learned about mingling disciplines such as human centered design, full stack engineering, and data science? And how are we taking an entrepreneurial approach to develop successful solutions that deliver real impact? Read more.
4:35pm–5:15pm Thursday, 10/01/2015
Location: 1 E6 / 1 E7
Tim Estes (Digital Reasoning)
Average rating: ****.
(4.67, 3 ratings)
Cognitive computing has made the transition from a theoretical technology into one that is having a transformative impact on business and our daily lives. In this session, Tim Estes, CEO and founder of Digital Reasoning, will explore how key enabling technologies, such as artificial intelligence and natural language processing, have made this possible. Read more.
4:35pm–5:15pm Thursday, 10/01/2015
Location: 1 E14
Join us to learn about how SAP HANA Vora can be used as a stand-alone or in concert with SAP HANA platform to extend enterprise-grade analytics to Hadoop clusters and provide enriched, interactive analytics on Hadoop. Read more.
4:35pm–5:15pm Thursday, 10/01/2015
Location: 1 E15
Michał Iwanowski (DeepSense.io), Piotr Piotr (deepsense.io)
With Spark becoming the rising star of cluster computing comes the prospect of putting it to use as a platform for end-to-end data science. At DeepSense.io we have built an intuitive interface to take Spark to the next level of usability. By introducing a layer that provides code-free UX and simplified resource management, Spark is brought even closer to the concepts known in data science. Read more.