Gestión de Datos y Analítica. Conferencia Denodo Datafest. (Live Streaming) - 19 de octubre de 2017 - TecnoWebinars.com

Modern data integration relies on fast data strategy - the ability to quickly make the data available to the business users in real-time.

Attend this session to learn:

• How to modernize your data integration
• How to create a data abstraction layer so that business users are insulated from underlying system changes
• Establishing a data services marketplace, so that developers can easily develop SOA applications

 Data virtualization, ETL and ESB technologies have a role in an organization’s integration strategy. Choosing the right tool for the right use case can be challenging.

Attend this session to learn:

• The distinct roles of data virtualization, ETL and ESB in the data integration paradigm
• How data virtualization complements ETL and ESB
• Customer case studies leveraging these technologies together

 According to Gartner, “By 2018, organizations with data virtualization capabilities will spend 40% less on building and managing data integration processes for connecting distributed data assets.” Data virtualization has become a critical piece of technology for any flexible and agile modern data architecture.

Attend this session to learn:

• What data virtualization is, and how it differs from traditional data integration approaches
• Key patterns and use cases of data virtualization
• Examples of business benefits realized by data virtualization customers

 PANEL: Alex Rosenthal Guardian Life / Paul Moxon Denodo / Partner 
MODERATOR: Ravi Shankar Denodo

This panel discussion is a follow-up to the sessions in the “Introduction to Data Virtualization” theme.

 Speed is everything. Businesses that move fast leave their competition in the dust. But one needs high performance architecture to enable it.

Attend this session to learn:

• How businesses can move faster than their competitors with the right architecture
• The critical technology component that enables speed and agility
• How to build a data services layer to protect the data sources from corruption

 Big data is like an abundant, expanding natural resource emerging from the modern data landscape. IoT, mobile, social, clickstream, web and open data are important contributors to the proliferation of data that we are witnessing today. Worldwide data is expected to increase tenfold by 2025—reaching a total of 163 ZB—according to a recent IDC-Seagate study.

Attend this session to learn:

• The challenges posed by modern data ecosystem
• The role of data virtualization in overcoming these challenges
• How to achieve technical cohesion and business value in a complex data ecosystem

 The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized repository. But this approach is slow and expensive, and sometimes not even feasible because of the distributed nature of data.

Attend this session to learn:

• Why logical architectures are the best option when integrating big data
• How Denodo’s parallel in-memory capabilities with dynamic query optimization redefine analytics architectures
• How IT can meet business demands for data much faster using data virtualization

 PANEL: Nagaraj Vijapurkar CIT Group / Alberto Pan Denodo / Partner 
MODERATOR: Saptarshi Sengupta Denodo

This panel discussion is a follow-up to the sessions in the “In-memory Fabric/Real-time” theme.

 Businesses are demanding more autonomy from IT to enable the creation the necessary reports and to perform analysis.

Attend this session to learn:

• How to create an environment that enables self-service
• How to architect an universal semantic model - a common business definition layer that simplifies integration
• Liberating the buisness users to use any reporting tool

 Business users come in all shapes and sizes. It’s imperative to understand who they are (e.g., data analysts, power users, executives or machines) and the data they need. Self-service initiatives can only be successful when business users’ views of the data are holistic, and consistent across distinct business functions.

Attend this session to learn:

• What universal semantic model is, and why it is critical for self-service initiatives
• Why data virtualization is the best-fit technology for data democratization
• How data virtualization enables self-service with guard rails

 Finding the right data within seconds is what matters most to analysts and decision makers. Data virtualization incorporates a rich business-user oriented information catalog and self-service interface to search, discover, model and collaborate.

Attend this demo to learn:

• How to find the right data efficiently, even when users are unfamiliar with the data models
• How to enrich the metadata with tags, annotations, and comments to foster collaboration
• How to discover relationships and associations in the data as well as to share the data responsibly

 PANEL: Kyle Quass Indiana University / Phoebe Bakanas Denodo / Partner 
MODERATOR: Paul Moxon Denodo

This panel discussion is a follow-up to the sessions in the “Self-Service BI” theme.

 Big data projects are becoming mature and consistent. However, they remain siloed compared to the enterprise data. In addition, now new streaming data needs to integrated as well.

Attend this session to learn:

• How big data projects can be combined with other enterprise data
• How to integrate streaming data into the mix
• Benefits of aggregating the data without having to move them into a centralized repository

 Big data optimization is a daunting task. The optimizer is one of the most complex parts of any big data engine; it must ensure that the execution engine is performing at its best, so understanding how it works is crucial.

Attend this session to learn:

• Challenges in working with big data workloads
• What is under the hood of the data virtualization optimization engine
• When, how, and why to use different optimization options

 The Internet-of-Things is further evolving into Internet-of-Anything. Organizations are empowering business users with actionable intelligence derived from data-in-motion, data-at-rest, and enterprise applications. Edge computing plays an important role in the IoT ecosystem since immediacy enables faster response to urgent conditions.

Attend this session to learn:

• How edge computing enables IoT-driven businesses
• The role of data virtualization in Internet-of-Anything
• Data virtualization and edge computing patterns

 PANEL: Arun Murugan GE Capital / Pablo Alvarez Denodo / Partner 
MODERATOR: Michael Papalos Denodo

This panel discussion is a follow-up to the sessions in the “Big Data / Edge Computing” theme.