Valerie Calvo is a Data Governance Manager for CBRE Investment Management, joining the firm in 2022. She directly supports data-driven ambitions by setting and realizing the firm’s Data Governance strategy and championing data democratization. In this role, she is responsible for ensuring consistent practices while creating processes for metadata management, reference data, and data quality management.

Immediately prior to joining CBRE IM, Valerie led a team responsible for the design and implementation of semantic models, reference data, taxonomies, and master data inventories as well as the enterprise adoption of data management practices at Bloomberg LP.

Valerie is an attorney admitted to practice in New York & New Jersey, graduating from the University of Miami School of Law and Rutgers College. She also holds Certificates in the Data Management Capability Assessment Model (DCAM) v2.2 (EDM Council) and Advanced Data Analytics (General Assembly).

Abstract

Considerable time and effort are devoted to developing and executing a data governance strategy. However, effective, and sustained communication is an often-overlooked critical factor. To formalize and foster a data-driven program and culture, organizations must remember to communicate clearly and often to drive buy-in and promote a two-way governance dialogue.

In this talk we’ll cover:

Why DG communication is important at all stages from program kick-off to business-as-usual;

• Different types of DG communication
• Components of CLEAR communication with examples to use in your own organization

Creative Lingo-free Efficient Applicable Regular

Where

RSVP for join code, this is an VIRTUAL event via Google Meet

Date – Thursday, July 20th

Noon – 1pm

Valerie Calvo is a Data Governance Manager for CBRE Investment Management, joining the firm in 2022. She directly supports data-driven ambitions by setting and realizing the firm’s Data Governance strategy and championing data democratization. In this role, she is responsible for ensuring consistent practices while creating processes for metadata management, reference data, and data quality management.

Immediately prior to joining CBRE IM, Valerie led a team responsible for the design and implementation of semantic models, reference data, taxonomies, and master data inventories as well as the enterprise adoption of data management practices at Bloomberg LP.

Valerie is an attorney admitted to practice in New York & New Jersey, graduating from the University of Miami School of Law and Rutgers College. She also holds Certificates in the Data Management Capability Assessment Model (DCAM) v2.2 (EDM Council) and Advanced Data Analytics (General Assembly).

Abstract

Considerable time and effort are devoted to developing and executing a data governance strategy. However, effective, and sustained communication is an often-overlooked critical factor. To formalize and foster a data-driven program and culture, organizations must remember to communicate clearly and often to drive buy-in and promote a two-way governance dialogue.

In this talk we’ll cover:

Why DG communication is important at all stages from program kick-off to business-as-usual;

• Different types of DG communication
• Components of CLEAR communication with examples to use in your own organization

Creative Lingo-free Efficient Applicable Regular

Where

RSVP for join code, this is an VIRTUAL event via Google Meet

Speakers

Mike Meriton, Co-Founder of EDM Council

Mike is a Co-Founder of the EDM Council and served as the first Chairman and active Board member since inception in 2005. Mike joined in 2015 as a Senior Advisor, promoted to COO in 2020, to lead Industry Engagement strategy, new member services and Council Operations.

Previously, Mike was the CEO of GoldenSource and held key executive roles at CheckFree (Fiserv), D&B and Oracle.

Jim Halcomb, Head of Product Management of EDM Council

Jim is Head of Product Management for the EDM Council. He is a strategy, data management, and cybersecurity executive with 30 years of international business experience. Jim has worked with the Council since its inception in 2005, eventually leading the initial research and development of the DCAM from late 2011 to 2014.

Abstract

Across all industries, firms are embracing cloud technologies to advance their digital transformation and business strategies. Yet there is a gap in understanding and applying the optimal data management capabilities required for successfully migrating and managing sensitive data in the cloud, and leveraging the cloud for data enablement to drive business value across the enterprise.

To address this issue, the EDM Council formed the Cloud Data Management Capabilities (“CDMC”) working group. The CDMC working group was managed by the EDM Council and co-chaired by Morgan Stanley and LSEG, with participation from the world’s top Cloud Service Providers (CSPs) AWS, Microsoft Azure, Google Cloud, IBM and 100+ leading cross-industry firms. CDMC v1.1 was released September 2021 and is now available to all companies and establishes a data risk governance and control framework for cloud, multi and hybrid cloud environments.

This discussion will dive into:

• What are the value drivers for CDMC?
• What results and progress are firms seeing by using CDMC?
• How does CDMC help with managing sensitive data in the cloud?
• What role does CDMC play in driving digital transformation?
• How does CDMC help CSP’s and other Technology providers?
• How does CDMC help accelerate trusted cloud adoption?

Where

RSVP for join code, this is an VIRTUAL event via Google Meet

Keith Belanger, SqlDBM Product Evangelist

Keith Belanger has over 27 years experience in the Data Architecture space and started his journey as a Data Modeler in the OLTP space and eventually migrated over to the OLAP space. He has had many roles over the years including ETL Development, BI Administration, DBA & Data Architecture. He was the Senior Data Architect and Director of Data Architecture for a Fortune 100 P&C Insurance Company. He also has consulted many companies in many verticals on their Data Modernization strategies. Keith is expert in Kimball (Star Schema) & Data Vault 2.0 solution strategies. Recognized Snowflake Data Superhero and board member of the Data Vault North America User Group.

Abstract In this presentation we will explore the benefits of top-down modeling approaches and emphasize the value of top-down modeling in data warehousing and highlight the importance of ontologies. We will discuss "why" top-down models should be considered, "how" to develop these models and apply it to your data warehousing initiatives. Ultimately, encouraging the adoption of top-down modeling as a flexible and forward-looking approach that can better meet the evolving needs of businesses while delivering tangible value.

RSVP for Google Meet link to be sent in advance, and available on the Eventbrite Online Event Page.

Semantic Layer Architecture: Top Applications and Implementation Approaches for Enterprise Data Management (with Real World Examples)

Over the last decade, we have seen some of the most exciting innovations emerge within the enterprise knowledge and data management spaces. Those innovations with real staying power have proven to drive business outcomes and prioritize intuitive user engagement. Within this list are a semantic layer (for breaking the silos between knowledge and data) and of course, generative AI (a topic that is often top of mind on today’s strategic roadmaps). Both have one thing in common—they are showing promise in addressing the age-old challenge of unlocking business insights from organizational knowledge and data, without the complexities of expensive data, system, and content migrations.

In 2019, Gartner published research emphasizing the end to “a single version of the truth” for data and knowledge management and that by 2026, “active metadata” will power over 50% of BI and analytics tools and solutions to provide a structured and consistent approach to connecting instead of consolidating data.

By employing semantic components and standards (through metadata, business glossaries, taxonomy/ontology, and graph solutions), a semantic layer arms organizations with a framework to aggregate and connect siloed data/content, explicitly provide business context for data, and serve as the layer for explainable AI.

This session will present case studies that take a deep dive in the technical architecture of a Semantic Layer, exploring the components that enable semantic capabilities, such as metadata management, data catalogs, ontology/knowledge graphs and AI infrastructure. The presentation will emphasize how these components interconnect organizational knowledge and data assets, enhancing systems like recommendation engines and semantic search and explore the top three common approaches we are seeing at play in order to weave this data and knowledge layer into the fabric of enterprise architecture, highlighting the applications and organizational considerations for each.

SPEAKERS

Lulit Tesfaye is a Partner and the Vice President for Knowledge & Data Services and Engineering at Enterprise Knowledge, LLC., the largest global consultancy dedicated to Knowledge and data management. Lulit brings over 15 years of experience leading global information and data management initiatives, specializing in technologies and integrations. Lulit is most recently focused on employing advanced Enterprise AI, knowledge graphs, and semantic layer capabilities for optimizing enterprise data and information assets.

Urmi Majumder is a Principal Architect at Enterprise Knowledge, where she leads system architecture, design, and implementation of a broad range of enterprise solutions. She has 15 years of experience leading the development of technical solutions in support of a wide variety of federal and commercial clients by integrating open-source, SaaS, and COTS tools and establishing the connection between these tools and their business users. Her diverse portfolio includes the design and development of data-centric solutions, including content management systems, record management systems, knowledge portals, search applications, semantic applications, data catalogs, and AI/ML applications, both in the context of new system development and data modernization efforts.