Big Data in the Cloud Conference. Big Data Working Group

Transcription

1 Big Data in the Cloud Conference + Big Data Working Group 1

2 CSCC Big Data in the Cloud Conference The Conference s goal is to help end-user organizations understand the current state and future directions of Big Data in the Cloud technology Presenters include senior representatives from end-users, vendors, standards groups, government, and industry organizations The CSCC Big Data Working Group will work with other organizations on future Conferences and the development of information resources for the Big Data community 2

3 CSCC Big Data Working Group: Scope This CSCC Working Group will build on cloud computing principles and end-user experiences to document best practices and identify functional and standards requirements for Internet-scale Big Data platforms.

4 Tasks for CSCC Big Data Working Group Collect high priority Big Data use cases Develop specific Big Data requirements for use cases Catalog Big Data design alternatives and principles Document best practice alternatives and standards for meeting specific requirements Identify gaps in capabilities and standards that should be addressed by vendors and standards groups Note that this is a a similar strategy to NIST s Cloud Initiative and will require collaboration with other organizations (e.g. NIST, SDOs)

5 Collect Big Data Application Use Cases Analysis Determine Big Data Requirements Matching Gap Analysis Planning Big Data Technology v Roadmap Catalog of Current Big Data Capabilities Planned Capabilities Capabilities Select Solutions Big Data Technology and Standards

6 CSCC Big Data Conference Morning Agenda 08:00 08:15 Welcome & Motivation (Bob Marcus - CSCC Big Data WG) 08:15 09:00 Federal R&D Big Data Initiative (George Strawn Director, NITRD) 09:00 09:30 Demystifying Big Data TechAmerica Report (Bill Perlowitz CTO Wyle) 09:30 10:00 Industry Impact of Big Data in the Cloud (Inhi Cho Suh VP, IM Strategy, IBM) 10:00 10:15 Break 10:15 11:00 Financial Opportunities in Big Data (Michael Versace Director, IDC Financial) 11:00 11:15 The Role of Standards in Big Data in the Cloud (Jamie Clark, General Counsel, OASIS) 11:15-12:00 NIST Perspective on BD in the Cloud (Ashit Talukder- Dir, NIST Info Access Div)

7 CSCC Big Data Conference Afternoon Agenda 01:00 01:15 Big Data Vendor Landscape (Matt Turck VC, Bloomberg Ventures) 01:15 03:15 Vendor Panel (Execs from Amazon, IBM, Microsoft, and Oracle) 03:15 03:30 Break 03:30 04:00 Security Implications of BD in the Cloud (Dr. Arnab Roy WG Leader, CSA) 04:00 04:30 Data Architecture of State Street Private Cloud (David Saul Chief Scientist, State Street) 04:30 05:00 Big Data for Energy Analytics (Mel Greer Chief Strategist, Lockheed Martin) 05:00 05:15 Wrap Up / Next Steps 05:15 05:30 Break 05:30 07:00 CSCC Big Data WG Kickoff (James Kobielus Co-Chair)

8 Backup Slides for Proceedings 8

9 CSCC Big Data Working Group: Background The convergence of big data and cloud enables enterprises to engage their customers in innovative ways. Enterprises are combining their core competencies and emerging customer engagement models (e.g., mobile, social, web) to establish new business models. The success of cloud-based business models depends upon the development and delivery of large internet-scale big-data services and platforms. These services are of enormous scale, are globally distributed, have varied work load profiles, and have increasing data volumes. The operational, technological, and business challenges faced by enterprises in successfully delivering these services are extremely challenging. To be successful, enterprises must adopt agile big-data analytics and cloud development best practices, where time-to-market and rapid, iterative technology development becomes critical enablers. The availability, performance, security and cost-effectiveness of big-data analytics applications are critically important. Unfortunately, most enterprises are hindered by the inefficiencies of their legacy big-data analytics systems.

10 CSCC Big Data Working Group: Objectives Define the key best practices and standards for deploying, optimizing, managing, securing, and evolving internet-scale big data analytics applications and platforms in the cloud; Help end-user organizations align their cloud-based big-data initiatives with key strategic imperatives in a fast-changing competitive and operational environment; Provide an ongoing forum for end-user organizations in diverse industries to discuss key issues, practices, standards, and frameworks for cloud-based big-data analytics specific to their environments and requirements; Build on and extend established industry use cases, best practices, standards, and frameworks in cloud computing (IaaS, PaaS, SaaS) and big data to identify functional/standards requirements for the nextgeneration cloud-based big-data platform; and Capture the characteristics of the new, engaging business models driving the shift toward cloud-based big-data analytics.