Big Data Boot Camp Agenda

The keynote presentation offers perspective into the dynamics and current issues being encountered in today’s Big Data analytic implementations. While best practices to guide the management and governance of Big Data continue to evolve, there are established approaches to leveraging Big Data to get the biggest impact and to drive a data-driven culture focused on responsibilities, outcomes, and insights. This presentation also covers the most important and strategic technologies currently emerging to meet the needs of the “Big Data Paradigm.”

REDEFINING BIG DATA: SURVEY INSIGHTS ON MARKET PRIORITIES

We've all read the definition of Big Data: variety, velocity, and volume, volume, volume. Through the latest market research this session will rethink what Big Data is, what the technical priorities are, and its impact on data management priorities.

This session presents a methodical approach for transforming complex heterogeneous IT environments to a Big Data-enabled ecosystem. Despite enormous interests and attempts of jumping on Big Data, a lot of Big Data IT activities have turned out to be ad hoc and experimental without long-term thinking and systematic planning. This session provides a comprehensive framework designed to formulate a maturity-driven and process-based method, comprising nine integral modules: Foundation, Applicability, Strategization, Taxonomy, Tooling, Road Map, Architecture, Convergence, and Knowledgebase.

This session provides an overview of high-performance databases and the price performance innovations that are now enabled by inexpensive hardware and memory delivering on the promise of real-time data and analytics. Several Big Data case studies focuses on data service providers and how they are leveraging Big Data, high-performance databases, and analytics to drive their business models.

This panel discusses how organizations are modernizing traditional data warehouses to accommodate Big Data and explores various options such as appliances, new high-speed databases, and cloud solutions.

Market Insights: The Next Generation of Database Technologies

Big Data is gaining a lot of attention around the world, but the phrase itself can be a misnomer. Too often, conversations focus on the "Big" when the real impact comes from the "Data." How do you turn data into actionable information to make better decisions, create new products or provide access to their citizens and customers? The key is how we store and manage the data - particularly complex, hierarchical metadata. Learn how a new generation of technologies: NoSQL, serialized search and Hadoop are impacting organizations of all sizes.

This session provides a brief introduction to Hadoop and includes several practical examples and case studies of how Hadoop is being used in the companies which have been traditional users of relational databases. This session also looks into the areas as ETL, archival storage, analytics, and other adoption scenarios commonly in use in many organizations today.

This session focuses on the area of multilayered self-calibrating analytics, which is the latest Big Data analytic technique for in-stream prediction on streaming transaction data. This technology leverages multilayered model architecture to obtain impressive model performance and robustness compared to traditional analytic techniques. The session also addresses streaming analytic applications and looks at applications of this technology related to payment fraud detection and new emerging transaction areas.

This session focuses on the legal and risk management challenges and priorities posed by Big Data. Data security, IT management, records management, and/or legal compliance are addressed along with how to properly mine, assemble, protect, and manage Big Data in order to meet today’s fast-changing requirements. Attendees also learn how to understand the risks, obligations, and standards required of anyone involved with Big Data. It explains the specific risks that can occur when data is missing, altered, or inadequately preserved, along with best practices for reducing or eliminating these risks. It also describes minimum standards for data integrity and privacy including encryption, storage, vendor obligations, and audits of security practices such as chain of custody.

This session focuses on the creation and management of a structured program designed for the social business enablement of 10% of a 6,000-person workforce at BMC Software. Best practices on how to develop an enterprise-wide social business program for training participants and encouraging adoption to compliance and measurement are discussed. Attendees reap the rewards of experience through case studies, tips, and insights gained along the journey to creating new levels of visibility for customers and employees. Finally, the end game of social business is garnering attention for the organization and driving business, and Hutchings explains how to understand and measure social media data to determine impact that social business has on the bottom line.

This session provides an overview of common issues and differences when it comes to managing Big Data in any industry: Telecom, financial and healthcare. An historical perspective of the database technology industry from the early ’80s is presented along with new emerging trends in Big Data and the cloud. History repeats itself; ISAM and the advent of RDBMS are discussed along with noSQL, newSQL, etc., and the fact that traditional database principles still remain. Venkatesan discusses the evolution of Big Data and provides a landscape on the pros and cons of all the technologies, frameworks, and players in Big Data today.

This session focuses on the increasing business requirements for sophisticated analytic reports from operational data within hours or even minutes. Attendees learn and explore how to load a data warehouse using low-impact log-based replication from SQL databases. Hodges uses MySQL to Vertica loading as an example and shows how to address the impedance mismatch between row- and column-oriented stores and enable real-time loading with maximal performance and minimal impact on working applications. Attendees learn practical ways to make data loading more efficient through good schema design, consistent character sets, time zone standardization, and more. A demonstration of replication using Tungsten open source replication is conducted during the session.

This session explores how organizations can best utilize today’s technologies to manage large data sets in an efficient, defensible, cost-effective manner; streamline e-discovery management; and discuss security concerns and case study examples. Tredennick also discusses the top challenges organizations face managing Big Data e-discovery, reviews the range of e-discovery technologies available to manage Big Data and factors to consider when choosing the right solution—including cloud vs. appliance, predictive analytics, and total cost of ownership. The session also examines why the cloud is key to managing massive data and the security factors to consider when utilizing cloud technologies.

Big Business with Big Data

Join Objectivity, Inc. as we discuss how to gain value from Big Data utilizing complementary graph database technology within your architecture. The session covers today's evolving real-time requirements, yesterday?s architecture, and how using complementary technologies within your solution stack can help you achieve the results for tomorrow.

As Big Data marches ahead, more and more of that information is unstructured, from tweets to PDFs, and the percentage of unstructured information stored in NoSQL engines is rising fast. This session explores the options for synthesizing structure in big document sets. How do I impose order on my text? What tools can I use to find my text? How do I leverage corporate knowledge and structure to make my text easier to find? The ubiquity of full- text search makes finding this unstructured information possible. But what is the next step? How do you make it even easier to find your unstructured information? This session also focuses on taxonomies, auto-tagging, and faceted navigation of search results.

This session focuses on the management of Big Data, and how, if managed well, it can actually help corporate counsel defend the actions of the organization. Dawson discusses in detail and utilizes case studies to demonstrate the legal and organizational value of Big Data and how to manage it for the corporate counsel.

The panel discusses the risk management and governance of Big Data in organizations and identifies the potential legal implications in the acquisition, management and archiving of Big Data. Panelists address and comment on a series of questions from attendees.

This session discusses the consequences of poor data quality in projects and demonstrates how small tweaks to people, process, and technology can lead to an agile approach to data management. Low-quality data leads to confusion, wasted resources, poor performance, and limited business value. The success of your project relies on strong governance practices, backed by a confident understanding of the root causes of your data quality problems. Often, large changes in complex systems can be traced back to small, seemingly harmless incidents. This is most apparent in Big Data, where inaccuracies and inconsistencies quickly grow into data quality problems that can threaten the success of your entire project.

Next-generation systems make it possible to extract high-value data from large flows of information from social media services and other types of systems, which only 5 years ago were not accessible to most organizations. The session reviews new systems and service providers (such as Cybertap, Datametrics, Lexalytics) and highlights their applicability to decision making, marketing, and information access. It's not enough to address the challenge big data brings to risk management, as Big Data also presents issues related to organizational management, finance, staff, and resources.