James Kobielus

Senior Director of Research for Data Management at TDWI

Extending the Data Fabric to the Multicloud

In this session, we will discuss the challenges of extending data fabrics throughout multicloud environments all the way to a multitude of edge devices.

TDWI’s James Kobielus will describe how to use data virtualization to support low-latency, event-driven, and streaming data applications across complex data clouds. He will discuss how to provide unified access to distributed data resources using virtualization in conjunction with serverless and containerized microservices. Plus, he will explain the role of AI-enabled data catalogs in delivering self-service discovery, access, and curation of data resources that are distributed across public, private, hybrid, and multicloud topologies.

Speaker Bio: James Kobielus is senior director of Research for Data Management at TDWI. He is a veteran industry analyst, consultant, author, speaker, and blogger in analytics and data management. At TDWI he focuses on data management, artificial intelligence, and cloud computing. Previously, Kobielus held positions at Futurum Research, SiliconANGLEWikibon, Forrester Research, Current Analysis and the Burton Group. He has also served as Senior Program Director, Product Marketing for Big Data Analytics for IBM, where he was both a subject matter expert and a strategist on thought leadership and content marketing programs targeted at the data science community.

Ravi Shankar

SVP and CMO, Denodo

Data Lakehouses: The Hype, Reality, and Why You still Need a Logical Architecture

Data lakehouses promise to deliver on all the benefits of data lakes and data warehouses, combined. The idea is that unstructured and structured data can live in one repository, equally supporting both data scientists and BI and analytics users, while lowering costs and also improving processing power and flexibility.

As much as the blend benefits, however, data lakehouses also combine the weaknesses of data warehouses and data lakes, and a logical data fabric is still a necessity to unlock the full value from these new cloud offerings. If big data is any indication, most large organizations never put all of their data into a single repository because of both the effort and cost involved.

In this session, Ravi will discuss the hype and reality of data lakehouses. He will describe how a data lakehouse figures into a logical data fabric. He will explain how a logical data fabric offsets the weaknesses of lakehouses, and he will go in-depth on data virtualization as an architectural core component of logical data fabrics.

Speaker Bio: Ravi Shankar is the senior vice president and chief marketing officer at Denodo. He is responsible for Denodo’s global marketing efforts, including product marketing, demand generation, field marketing, communications, social marketing, customer advocacy, partner marketing, branding, and solutions marketing.

Ravi brings to his role more than 25 years of proven marketing leadership and product management, business development, and software development expertise within both large and emerging enterprise software leaders such as Oracle, Informatica, and Siperian. His deep expertise in data-related technologies facilitates increased global awareness of the Denodo Platform and accelerates its growth.

Ravi holds an MBA from the Haas School of Business at the University of California, Berkeley, and an MS and an Honors BS degree in computer science. He is a published author and a frequent speaker on data management and governance. Prior to joining Denodo, Ravi was the vice president of product marketing at Informatica and was instrumental in positioning the company as a leader in the master data management (MDM) market. He helped accelerate MDM revenue and customer acquisition, and helped propel Informatica into a $1B company.