Data Summit


Data Summit Program, Sept. 22, 2016

Data Science Revolution!

PG MadhavanPG Madhavan
Executive Chairman Syzen Analytics

Data Science as the next “industrial revolution”; roles of AI & IA; future of Analytics; why businesses need predictive Analytics; Data Science roles; a new Independent Analytics Vendor business model. In this talk, we develop a unified approach to Data Science and Machine Learning and sketch out a roadmap of increasingly complex solutions. The tools developed provide us with high-value features in terms of system parameters, a framework for closed-loop real-time Analytics and ways to possibly accommodate the network-graph nature of data sources. A retail commerce example is followed through out to clarify the power of Systems Analytics.

About PG Madhavan

PG is a true "algorist" who developed his expertise as a University of Michigan EECS Professor, Computational Neuroscience researcher, Bell labs MTS, Microsoft Architect and multiple startup leader. He has over 100 publications & platform presentations to Sales, Marketing, Product, Standards and Research groups as well as 12 issued US patents.


The Skeleton Key to Data Analytics

Will Hayes Will Hayes

By 2020, the total amount of data will reach 44 zetabytes, in the form of logs, Hadoop clusters and information from an exploding number of IoT devices. Despite the craze to get “data-driven,” most organizations haven’t figured out how to create actual value from their data. So how can you put your data to work? Search. The ability to retrieve and make sense of information is the most important action for manifesting Big Data’s promise. In this session, Will Hayes will cover how search technology enables information access like never before, and how to take advantage within your own business.

About Will Hayes

Will Hayes is CEO of Lucidworks, a San Francisco-based enterprise search company backed by the world’s strongest and most active open source search community, Apache Solr. Lucidworks provides the search platform for global brands, delivering the enterprise-grade capabilities needed to design, develop, and deploy intelligent search apps at any scale. Companies across industries—from consumer retail and healthcare to insurance and financial services—rely on Lucidworks every day to power their consumer-facing and enterprise search apps. Previously, Will held product and business development positions at big data analysis company Splunk and biotech firm Genentech.

Opportunities and Pitfalls of Big Data

Ken Mallon Ken Mallon
Chief Product Officer

Big Data has become little more than a throw-away buzzword, thanks to the proliferation of data across industries and lack of ability to use that data in a meaningful way. Healthcare, defense, biomedicine, social media, and retail are all producing virtually infinite streams of data, but these industries had not seen the cascading benefits initially expected through analysis of “Big Data.” A primary contributor to this data deluge is the steady stream shared and collected by smartphones. This session covers opportunities and pitfalls of this data stream, and harnessing the power of mobile to deliver results for national brand advertisers.

About Ken Mallon

Ken Mallon is chief product officer at 4INFO, after various leadership positions in Technology, Market Research and Biotech. Since 2000, Ken has focused exclusively on digital advertising. Ken led teams at Yahoo that helped bring behavioral targeting to the market, along with the first closed loop targeting/offline sales systems. At Dynamic Logic, Ken helped expand survey-based ad effectiveness solutions and led the development of the world’s largest brand impact normative database. At Yahoo! Labs, he innovated hyper-local targeting technology. Ken led Measurement & Insights products for Microsoft. Ken holds advanced degrees in quantitative science fields from Stanford and Johns Hopkins.

Data-driven Decision Making for Long-term Product Success

Ahmad Anvari Ahmad Anvari
Product/analytics Leadership

In this talk, we will go through principals of data-driven decision making, with several examples of successful and unsuccessful decisions based on data. We will also cover best practices and common mistakes that could cost companies billions of dollars in lost opportunity.


About Ahmad Anvari

Ahmad Anvari leads the Messenger business and platform analytics team at Facebook. Prior to that, he had various product management and analytics leadership positions at Instagram, Google, Yahoo, and AOL/ Ahmad has a Masters in software engineering management from Carnegie Mellon university.



Unlocking the Business Value From IoT Analytics

Mohan Krisnamurthy Mohan Krisnamurthy
Senior Product Manager

Unlocking the business value of data generated from IoT devices requires the confluence of people with advanced analytical skills and advanced analytics platform. From reducing operational costs, to increasing revenue, to improving product design, are few of the benefits enterprises can experience by extracting insights from IoT analytics data. However, the volume, velocity and the variety of IoT data presents infrastructure as a bottleneck to analysis and insights.

About Mohan Krisnamurthy

Mohan Krisnamurthy is a Senior Product Manager at Qubole, where he is developing solutions focused on the Internet of Technologies in the energy and the transportation sectors.
Mohan has a background in mechanical engineering and controls and has worked with auto manufacturers and trucking fleets in improving fuel efficiency and reducing emissions. He was part of the research group at West Virginia University that conducted the emissions study exposing the Volkswagen scandal.Mohan has a Ph.D. in Mechanical Engineering from West Virginia University, and an MBA from UC Berkeley’s Haas School of Business.

pitfalls of data science teams and their integration in industries

Pedro Alves Pedro Alves
Director of Data Science
Sentient Technologies

This talk will focus on how people's natural inclination towards making assumptions are constantly in the way of finding the right solutions to problems, including in data science. This will include a practical overview of pitfalls of data science teams and their integration in industries.

About Pedro Alves

Pedro has experience in predicting, analyzing and visualizing data in the fields of: genomics, gene networks, cancer metastasis, insurance fraud/costs, hospital readmissions, soccer strategies, joint injuries, social graphs, human attraction, spam detection and topic modeling, among others. Pedro is incredibly passionate about all aspects of data science and is constantly creating new techniques and algorithms to suit the problems at hand. Pedro also has a strong attraction to the basics, which can be forgotten easily these days, such as the scientific method and just looking at the data. Recently his efforts were geared towards detecting and interpreting everything that is happening in the world in real-time, from major concerts and sporting events to major and minor news. Now he leads the data science efforts at where they use evolutionary algorithms and massively scaled deep learning to solve problems such as trading and visual comprehension of consumer products.

Strategies and Trends: Cloud Data Warehousing and Big Data

Hannah Smalltree Hannah Smalltree

Enterprises are moving more data warehousing and big data project into cloud-based processing
environments. Some are focused on cutting costs, others are driven by the promise of more agile big
data analytics. However, for many companies, there are new technologies to learn, new challenges to
understand and decades of existing on-premises investments to consider. In this executive-level talk:
Learn more about the many emerging technologies and “as a service” options for cloud data processing
Hear a roundup of recent industry research and cloud case studies
Get advice and evaluation considerations for designing a cloud strategy

About Hannah Smalltree

Hannah Smalltree is a director with Cazena. She contributes independently to industry research projects
and spent over a decade as technology journalist, interviewing hundreds of data and analytics
professionals. Hannah has also worked on product teams for several big data and data warehousing
companies, and brings a unique, unbiased perspective to her interactive presentations.

Rethinking Architectural Models With High Value Approximation

Jeff Kibler Jeff Kibler
VP, Technical Services

Data lake volume growth continues to increase momentum, and projections suggest we are on the cusp of hitting the wall with current architectural approaches. The days of “adding another node” are numbered, and the increase in complexity requires an evolutionary approach. This session explains Approximate Query Processing (AQP) and shows how high value approximations provide equivalent insight to exact queries while ensuring SLAs and reducing resource utilization. Using statistical metadata offers an opportunity to overcome the mounting scale barriers and increased complexity by rethinking the strategy and reaching previously unattainable opportunities.

About Jeff Kibler

Jeff Kibler joined Infobright in 2010. As Vice President, Technical Services, Jeff oversees all technical field elements including proof of concepts, training, post-sales support, IoT partnerships, and community.Jeff brings more than 12 years of big data software experience such as previously leading data quality at Yahoo!’s massive audience data pipeline. Utilizing Hadoop and other emerging data technologies, Jeff co-developed and released an end-to-end data pipeline auditing system to detect issues and alert stakeholders on data quality anomalies.

Data Danger Zone

Tamara Dull Tamara Dull
Director of Emerging Technologies for SAS Best Practices
SAS Institute

It's exciting times in the world of data. Executives are not only realizing data is a valuable corporate asset, they are also starting to pay attention to the opportunities data presents. The value in the use of data is getting the limelight is has long since deserved. But be careful. With this new excitement for data comes new challenges.
Advancements in technology provide powerful capabilities for companies to know more about and provide more for their customers than ever before. But, just because they can doesn’t mean they should. With the increased use of data throughout the business, the risks of unethical data use, intentional and unintentional, are growing exponentially. Companies must position themselves as trusted guardians of customer data and apply ethical standards around data driven decisions to ensure integrity and protect their public image.

About Tamara Dull

Tamara Dull is the Director of Emerging Technologies for SAS Best Practices, a thought leadership team at SAS. Through provocative articles and publications, and key industry engagements, she delivers a pragmatic perspective on big data, the Internet of Things, open source, privacy, and security. Tamara began her high tech journey long before the internet was born, and has held both technical and management positions for multiple technology vendors, consultancies, and a non-profit. She was recently listed in the Big Data 2016: Top 100 Influencers and Brands list and The Top 100 Big Data Experts to Follow in 2016.

Healthcare’s Data Journey

Rajib Ghosh Rajib Ghosh
Chief Data Officer
Community Health Center Network

Outside of the public health surveillance space where the practice of data collection and reporting goes back many years, data driven decision phenomenon in health care is relatively new. Interestingly physicians are well accustomed to make data driven decision making – they run the algorithm in their heads based on patient reported data points. They take those data in their branching logic. However, systematic data capture, analysis, reporting and insight generation and that too system wide at scale is a more recent phenomenon. Significant barriers still exist in making data with unquestionable quality available and actionable at the point of care. Adoption of data analytics is also uneven between larger and smaller health care organizations or between for-profit and not-for-profit community based organizations. This talk will take the audience through healthcare’s data journey: past, present and the future. It will also highlight successes and challenges. Disclaimer: Information shared in this talk will be speaker’s personal opinion and does not necessarily shared by the views and opinions of his employer.

About Rajib Ghosh

Rajib is an executive, entrepreneur, technology advisor and columnist.  Currently he is the Chief Data and Transformation Officer at Community Health Center Network (CHCN), a risk bearing Medi-Cal Managed Care organization based in the Alameda County, California, where he is responsible for Data Analytics and digital technology enabled transformation of the network.  CHCN and its network of community health centers take care of more than 200,000 underserved patients in the East Bay area. Rajib also advises digital health start-ups.  Prior to his current role he held senior product and program management positions at Hill-Rom, Solta Medical and Bosch Healthcare and launched many successful products globally generating $100+ million revenue.  Before that he worked as a consultant for global companies like Caterpillar, Nortel, CSX Transportation, and Marconi Telecom.Rajib has several publications and writes a regular column on healthcare analytics in the Analytics magazine published by INFORMS.  He also has publications in IEEE and ACM.Rajib has a BS in Electrical Engineering, MS in Computer Science and a MBA from the University of North Carolina, Chapel Hill.

Data Analytics in Patient-centered Healthcare

Colleen E CrangleColleen E Crangle
Founder/Associate Professor

Patient-centered healthcare is transforming the way we approach prevention, health and wellness. At the center is data, collected from patients and their environment. Continuous capture and transfer of mobile-based sensor data permit patient monitoring at home. Aggregated data analysis provides new ways to diagnose disease and track adverse events. Social media disclose patterns of behavior and reveal the wisdom of patients as they share their experiences. The full panoply of data challenges come into play, from incomplete data to real-time processing demands and privacy concerns. This talk will present the transformative potential of data analytics in patient-centered healthcare.

About Colleen E Crangle

Dr. Crangle has over 25 years’ experience in computer applications in healthcare. Current research involves the analysis of textual, acoustic, brain, and behavioral data from patients. She has a PhD from Stanford University and is a Senior Partner in Converspeech LLC.



IoT Security using Data Analytics

May Wang May Wang
Co-founder & CTO

Security risks are multiplying with even the most basic devices now becoming network-aware. Traditional signature-based security solutions often fail to protect such diverse IoT infrastructure. We will present our discoveries at ZingBox using real data and our innovative solution to address new challenges of IoT security. Our cloud based solution uses machine intelligence to identify, analyze and secure enterprise IoT deployments without any footprint on the IoT devices.

About May Wang

Dr. May Wang is Co-founder and CTO of ZingBox, an Internet of Things (IoT) security company. May is also an advisor for several PE/VC firms and startups, and an investor at Stanford Angels. Before ZingBox, May was the Head of Asia Pac Research and a Principal Architect in Cisco CTO office, leading IoT innovation. She was one of the organizers and speakers of the IoT World Forum 2014. Her innovation results are deployed in multiple Cisco’s best-selling products, including most of Cisco switches for data analysis and security. May received her Ph.D. from Stanford University in Electrical Engineering.

A Secure Network Infrastructure for Mission Critical Data from Industrial IoT

Ron Victor Ron Victor
Co Founder & CEO

In a truly connected world, the promise of the IoT value proposition comes out only when multiple applications have access to the same device data on a real-time basis so as to influence the application eco-system. These applications will reside everywhere - some on the cloud, some on the edge, some on-prem, some in public clouds, some in private clouds. Each application will have its own criteria for policy making on the same data i.e. some application may request data from the same device every hour, while another may want that data every minute. Some applications may want the data based on certain data value constraints (ex. < or > x)Some applications may want data from multiple silo'd device systems simultaneously while others may not. Some applications will be forced to reside on the edge of the IoT network while others elsewhere. What this situation creates is a fundamental problem of how can data be transported securely from any device to any number of applications simultaneously while allowing each application its own discrete policy making criteria on the same data .It calls for a secure, flexible and scalable network infrastructure that can support such a requirement for billions of devices in any vertical.

About Ron Victor

Ron Victor is a silicon-valley based technology entrepreneur with 20 years of experience and expertise launching new ventures at start-ups and fortune 1000 technology companies. To-date he has enabled raising more than $30Million in start-up capital for multiple start-ups in silicon-valley. Ron has founded and led three companies to-date with successful exits. His latest venture is IoTium Inc. – a Silicon Valley start-up that provides a secure, cloud-managed, easy-to-deploy software defined network infrastructure for all IoT verticals. IoTium’s  secure, horizontal, dynamically-configurable and scalable IoT network infrastructure solution significantly reduces the complexities for any IoT deployment including  smart cities, smart grids, building automation, energy installations, industrial automation, transportation and more. Prior to launching IoTium, Ron was Vice President of Marketing and Business Development of Wireless Industrial Technologies, an Industrial IoT company providing IoT solutions for heavy industry such as Aluminum smelters, Copper tank houses and more. Ron’s experience and expertise cover a vast range of activities ranging from global business development, strategic planning, sales and marketing, intellectual property and engineering development. His domain experience and expertise includes, IoT, Wireless Networking, VoIP, Streaming Media and Broadband.

Convergence of Silicon, Sensors, Mobility, and Cloud as Driving, Forces in System Design Evolution

Serge Leef Serge Leef
Vice President of New Ventures
Mentor Graphics

IoT is a huge emerging space that promises to deliver billions of connected devices to the consumers. Experience with general internet security and perspectives from the Government and Defense industry suggest that this wave of technology will likely be wide open to cyber attacks and both software and hardware levels. This speech examines the intersection points between IoT and secure silicon.

About Serge Leef

Serge Leef is the Vice President of New Ventures and General Manager of the System-Level Engineering Division. He is responsible for identifying and developing product opportunities for EDA in adjacent, systems-oriented markets. In addition to early stage programs, Serge leads on-going businesses focused on markets where system-level design plays a pivotal role: cyber-physical system design, systems engineering, design data management, cloud-based electronic design, IoT infrastructure, and hardware cybersecurity.  Serge serves on the Electrical and Computer Engineering Strategic Advisory Board at North Carolina State University.  In the past, he was a member of Oregon's Engineering and Technology Industry Council (ETIC) which advises the state's public university system on engineering, computer science and technology programs. Prior to joining Mentor Graphics in 1990, he was responsible for design automation at Silicon Graphics, where his team created revolutionary high-speed simulation tools to enable design of high speed 3D graphics chips that defined state-of-the-art in visualization, imaging, gaming and special effects for a decade. Before 1987, Leef managed a CAE/CAD organization at Microchip Inc. From 1982 to 1987 Serge worked at Intel Corp. developing functional and physical design and verification tools for major 8- and 16-bit microcontroller and microprocessor programs. Serge holds a BS in Electrical Engineering and MS in Computer Science from Arizona State University.

Why GPUs Will Transform Enterprise Analytics

Todd Mostak Todd Mostak

The GPU age is upon us. Having made the improbable jump from the game console to the supercomputer, GPUs are now invading the datacenter. By boasting order of magnitude performance improvements on key tasks and exhibiting massive cost of ownership advancements these once specialized chips are writing a new chapter in enterprise computing. Advanced analytics are the poster child for this transformation. As datasets have grown and visualization become more complex, CPU driven solution performance has deteriorated - resulting in lenghtly wait times for queries or risk inducing downsampling. This technical talk will discuss how GPU-tuned databases can improve performance by as much as 1000X and what techniques are required to deliver those speeds.

About Todd Mostak

CEO/Founder Todd Mostak first developed a prototype of MapD while waiting hours and sometimes days for a single query to process patterns in hundreds of millions of tweets for his Harvard thesis on the Arab Spring. Frustrated that he couldn’t access a cluster of computers to perform his computations, he created his own solution by pairing off-the-shelf video game GPU cards with a new design for parallel databases. With the encouragement of MIT/CSAIL advisor Sam Madden and Michael Stonebraker, Todd went on to found MapD in 2013. MapD is funded by Google Ventures (GV), Nvidia, Vanedge Capital and Verizon Ventures. Todd is a frequent industry speaker having given talks at Strata+Hadoop, Nvidia's GPU Technology Conference and others.

Big Data Strategy & Governance for Corporations & Nations

KRS Murthy KRS Murthy
i3 World

This talk explores the much needed understanding of the big data strategy at corporate level to the attendees, and covers the big data governance both at strategic level, and examples of data governance implementations. The speaker will address, first at conceptual levels, the relationship and mutual relevance between corporate governance and big data governance. Big data governance' is a subset and component of the corporate governance. The corporate holistic strategy and governance, the realm of the BOD of the corporation, should include big data strategy and governance.

About KRS Murthy

Dr. KRS Murthy is a multi-talented industry and academia veteran. He has been active in a wide variety of topics from technology to politics to poetry and music. He has been in particular very active in the area of Big Data. He has done keynotes, and been the chair and moderators for countless number of events. For a complete list of his activities and interest see: