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Conference Program: SIGMOD Sessions

This page describes the complete SIGMOD Conference program. Please use the following links to skip to the sessions of interest:

 

KEYNOTE TALKS AND PANEL

Keynote Talks

Keynote 1: How I Learned to Stop Worrying and Love Compilers

Eric Sedlar, Oracle Research
Tuesday 8:20-10:00
Location: Ballroom
Hashtag: #sigmod14 #keynote1
Session Chair: M. Tamer Özsu, University of Waterloo

Keynote 2: Fun with Hardware Transactional Memory

Maurice Herlihy, Brown University
Wednesday 8:30-10:00
Location: Ballroom
Hashtag: #sigmod14 #keynote2
Session Chair: Gustavo Alonso, ETH Zürich

Panel

Should we all be teaching “Intro to Data Science” instead of “Intro to Databases”

Wednesday 17:10-18:50
Location: Ballroom 2
Hashtag: #sigmod14 #panel1
Presenters: Bill Howe, University of Washington; Michael Franklin, University of California, Berkeley; Juliana Freire, New York University; James Frew, University of California, Santa Barbara; Tim Kraska, Brown University; Raghu Ramakrishnan, Microsoft Corporation

Are We Experiencing a Big Data Bubble?

Thursday 13:30-15:10
Location: Ballroom 2
Hashtag: #sigmod14 #panel2
Presenters: Fatma Özcan, IBM Almaden Research Center; Nesime Tatbul, Intel Labs and MIT; Daniel J. Abadi, Yale University; Marcel Kornacker, Cloudera; C Mohan, IBM Almaden Research Center; Karthik Ramasamy, Twitter, Inc.; Janet Wiener, Facebook, Inc.

SIGMOD RESEARCH SESSIONS

Research 1: Transaction Processing

Tuesday 10:30-12:10
Location: Superior
Hashtag: #sigmod14 #R1Px
Session Chair: Andy Pavlo, Carnegie Mellon University

Research 2: : Social Networks I

Tuesday 10:30-12:10
Location: Ballroom 1
Hashtag: #sigmod14 #R2Px
Session Chair: : Laks Lakshmanan, University of British Columbia

Research 3: Spatial Data

Tuesday 10:30-12:10
Location: Ballroom 2
Hashtag: #sigmod14 #R3Px
Session Chair: Lei Chen, Hong Kong University of Science and Technology

Research 4: Streams and Complex Event Processing

Tuesday 13:30-15:10
Location: Superior
Hashtag: #sigmod14 #R4Px
Session Chair: Badrish Chandramouli, Microsoft

Research 5: Data Analytics

Tuesday 13:30-15:10
Location: Ballroom 1
Hashtag: #sigmod14 #R5Px
Session Chair: Gottfried Vossen, University of Münster

Research 6: Graph and RDF Data Processing

Tuesday 13:30-15:10
Location: Ballroom 2
Hashtag: #sigmod14 #R6Px
Session Chair: Ioana Manolescu, Inria Saclay

Research 7: Multidimensional Data

Tuesday 15:40-17:20
Location: Superior
Hashtag: #sigmod14 #R7Px
Session Chair: David Maier, Portland State University

Research 8: Data Cleaning

Tuesday 15:40-17:20
Location: Ballroom 1
Hashtag: #sigmod14 #R8Px
Session Chair: Bogdan Cautis, Universite Paris Sud

Research 9: Data Exploration

Tuesday 15:40-17:20
Location: Ballroom 2
Hashtag: #sigmod14 #R9Px
Session Chair: Dennis Shasha, New York University

Research 10: Crowdsourcing

Wednesday 10:30-12:10
Location: Ballroom 1
Hashtag: #sigmod14 #R10Px
Session Chair: Timos Sellis, RMIT University

Research 11: Parallel Graph Processing

Wednesday 10:30-12:10
Location: Ballroom 2
Hashtag: #sigmod14 #R11Px
Session Chair: Xin Luna Dong, Google

Research 12: Potpouri

Wednesday 10:30-12:10
Location: Ballroom 3
Hashtag: #sigmod14 #R12Px
Session Chair: Feifei Li, University of Utah

Research 13: Data Management over Modern Hardware

Wednesday 15:00-16:40
Location: Ballroom 1
Hashtag: #sigmod14 #R13Px
Session Chair: Ryan Johnson, University of Toronto

Research 14: Non-traditional data

Wednesday 15:00-16:40
Location: Ballroom 2
Hashtag: #sigmod14 #R14Px
Session Chair: Florin Rusu, University of California, Merced

Research 15: MapReduce Processing

Wednesday 15:00-16:40
Location: Ballroom 3
Hashtag: #sigmod14 #R15Px
Session Chair: Konstantinos Karanasos, IBM Almaden Research Center

Research 16: Distributed and Parallel Data Management

Wednesday 17:10-18:50
Location:Superior
Hashtag: #sigmod14 #R16Px
Session Chair: Alfons Kemper, Technical University of Munich

Research 17: Graph Analytics

Wednesday 17:10-18:50
Location: Ballroom 1
Hashtag: #sigmod14 #R17Px
Session Chair: Wook-Shin Han, Pohang University of Science and Technology

Research 18: Query Processing and Optimization I

Wednesday 17:10-18:50
Location: Maybird
Hashtag: #sigmod14 #R18Px
Session Chair: Tim Kraska, Brown University

Research 19: Storage and Indexing

Thursday 10:30-12:10
Location: Superior
Hashtag: #sigmod14 #R19Px
Session Chair: Carsten Binnig, Cooperative State University Baden-Wuerttemberg, Mannheim

Research 20: Top-k Query Processing

Thursday 10:30-12:10
Location: Ballroom 1
Hashtag: #sigmod14 #R20Px
Session Chair: Jiaheng Lu, Renmin University of China

Research 21: Entity Matching

Thursday 10:30-12:10
Location: Ballroom 2
Hashtag: #sigmod14 #R21Px
Session Chair: Ihab F. Ilyas, University of Waterloo

Research 22: Query Processing and Optimization II

Thursday 13:30-15:10
Location: Superior
Hashtag: #sigmod14 #R22Px
Session Chair: Nikolaus Augsten, University of Salzburg

Research 23: Processing Dynamic Graphs

Thursday 13:30-15:10
Location: Ballroom 1
Hashtag: #sigmod14 #R23Px
Session Chair: Ambuj Singh, University of California Santa Barbara

Research 24: Cloud Computing

Thursday 13:30-15:10
Location: Ballroom 3
Hashtag: #sigmod14 #R24Px
Session Chair: Sudipta Das, Microsoft Research

Research 25: Security and Privacy

Thursday 15:40-17:20
Location: Superior
Hashtag: #sigmod14 #R25Px
Session Chair: Divesh Srivastava, AT&T Labs - Research

Research 26: Join Processing

Thursday 15:40-17:20
Location: Ballroom 1
Hashtag: #sigmod14 #R26Px
Session Chair: Curtis Dyerson, Utah State University

Research 27: Social Networks II

Thursday 15:40-17:20
Location: Ballroom 2
Hashtag: #sigmod14 #R27Px
Session Chair: H. V. Jagadish, University of Michigan

Research 28: Big Data

Thursday 15:40-17:20
Location: Ballroom 3
Hashtag: #sigmod14 #R28Px
Session Chair: K. Selçuk Candan, Arizona State University

SIGMOD TUTORIAL SESSIONS

SIGMOD INDUSTRY SESSIONS

Industry 1: Real-time/Complex Data Analytics

Tuesday 10:30-12:10
Location: Ballroom 3
Hashtag: #sigmod14 #I1Px
Session Chair: Nesime Tatbul, Intel Labs and MIT

Industry 2: Query Optimization

Tuesday 13:30-15:10
Location: Ballroom 3
Hashtag: #sigmod14 #I2Px
Session Chair: Fatma Özcan, IBM Almaden Research Center

Industry 3: Storage Management

Tuesday 15:40-17:20
Location: Ballroom 3
Hashtag: #sigmod14 #I3Px
Session Chair: Hakan Hacigumus, NEC Labs

Industry 4: Big Data Systems

Thursday 10:30-12:10
Location: Ballroom 3
Hashtag: #sigmod14 #I4Px
Session Chair: Shel Finkelstein, SAP Labs

SIGMOD DEMONSTRATION SESSIONS

SIGMOD Demonstrations, Group A

Wednesday 10:30-12:10, Thursday 15:40-17:20
Location: Wasatch
Hashtag: #sigmod14 #demoAx

SIGMOD Demonstrations, Group B

Wednesday 15:00-16:40, Thursday 10:30-12:10
Location: Wasatch
Hashtag: #sigmod14 #demoBx

SIGMOD Demonstrations, Group C

Wednesday 17:10-18:50, Thursday 13:30-15:10
Location: Wasatch
Hashtag: #sigmod14 #demoCx

SIGMOD SPONSOR EVENT TRENDING NOW

Wednesday 17:10-18:50
Location: Ballroom3
Session Chair: Feifei Li, University of Utah

Talk 1: Elements of Big Data Architecture

Speaker: Ryan Plant; Vice President, PWM Exception Processing, Goldman Sachs

What does Big Data architecture look like? When thinking of a strategic data management roadmap, where would you start? How would you leverage existing data sources and combine them with so-called “Big Data” technologies? How do you derive value from a Big Data solution? These are some of the fundamental questions that we will be answering as we present a Reference Architecture for Big Data. We will explore the key elements that any big (or small) data management platform should consider when embarking on a Big Data solution.

Talk 2: Performance Isolation in Microsoft Azure DB

Speaker: Vivek Narasayya; Principal Researcher, Microsoft Research

Microsoft Azure DB (formerly SQL Azure) is a multi-tenant, relational database-as-a-service. A consequence of multi-tenancy is the impact on performance of a tenant's workload by "noisy neighbors". We will describe the challenges and opportunities, and how Microsoft Azure DB addresses this problem today.

Talk 3: Oracle 12c Database In-Memory

Speaker: Tirthankar Lahiri; Vice President, Oracle Data Technologies and TimesTen

Oracle Database In-Memory extends industry-leading Oracle Database 12c with in-memory columnar technology featuring highly optimized in-memory column formats and SIMD vector processing, enabling analytics at a rate of billions of rows per second per CPU core. Column format is optimal for analytics while row format is optimal for OLTP. Oracle Database In-Memory employs a unique dual format architecture to allow real-time analytics against data being actively modified by OLTP applications. Since Oracle Database In Memory is seamlessly built into the Oracle Database Engine, all of Oracle’s extensive features, data types, interfaces and high availability mechanisms continue to work transparently. Enabling Oracle Database In-Memory is as simple as flipping a switch, and requires no application changes. Oracle Database In-Memory can both scale-up to the world's largest SMP's with thousands of CPU threads, as well as scale-out across fault-tolerant clusters using Oracle's proven RAC clustering technology. Furthermore, Oracle Database In-Memory does not require that all data fit in memory: In-memory column formats can be used for hot, actively accessed data while less active data can be tiered across much lower cost flash and disk storage, providing a cost-effective solution for very large databases.

SIGMOD POSTER SESSIONS

SIGMOD NEW RESEARCHER SYMPOSIUM

Successful Research: Planning, Collaborating, and Executing
Tuesday 17:30-19:00
Location: Ballroom
Hashtag: #sigmod2014 #research_symp
Session Chairs: Alexandra Meliou, University of Massachusetts Amherst; Anish Das Sarma, Troo.Ly, Inc.

Every year, the SIGMOD Conference includes an exciting symposium addressing various aspects of starting a career in the data management community. These symposia are geared towards graduate students and junior researchers, but they attract a very broad audience because they are both informative and entertaining. Each panelist gives a 10-minute presentation, based on their personal experiences and perspectives gained over the years. After the presentations, an informal discussion ensues, where questions are welcomed from the audience.
This year's panel will address the topic: "Successful Research: Planning, Collaborating, and Executing". The panel will discuss various aspects of planning out and executing successful research, with a focus on pursuing and establishing successful collaborations. This topic is of particular interest to graduate students and junior researchers, but is relevant to the entire data management community.

CAREERS IN INDUSTRY

Careers in Industry
Tuesday 19:15-20:15
Location: Ballroom
Hashtag: #sigmod2014 #industry_career
Session Chair: Cong Yu, Google Research.

Every year, the SIGMOD Conference also includes industry sessions and industry sponsors from industry leaders on big data management, database systems, and data management in general. Many students after graduation will join these companies and start an exciting career in industry. This year, the SIGMOD Conference organizes a career in industry panel event to address various aspects of starting a career in the data management industry. Each platinum or gold sponsor of the conference will send a representative to participate this panel. This year’s event consists of representatives from Goldman Sachs, Oracle, Microsoft, AT&T, Baidu, Facebook, Google, IBM Research, Pivotal, SAP, Tableau, and Walmart Labs. This event is geared towards undergraduate and graduate students and junior researchers, but we expect it to attract a very broad audience because it will be both informative and entertaining. Each panelist gives a short introduction, based on their personal experiences and perspectives gained over the years. After the introduction, an informal discussion ensues, where questions are welcomed from the audience.
The panel will discuss various aspects of preparing, planning out, and executing a successful industry career. This topic is of particular interest to undergraduate and graduate students, but is relevant to the entire data management community.

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