Ignite Your Insights

Course Overview

This course has a number of speakers covering Data Mesh and Data Vault, with the latest updates from our WWDVC 2023 conference sessions.. Paul Rankin from Roche kicks it off with a real-case study around their journey into Data Mesh, he describes why and how their teams come together.  He…

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Course Lessons

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Speaker: Jennifer Stirrup

Keynote: Unraveling Data Vault, Data Mesh, and Data Fabric

Stirrup is the founder and CEO of Data Relish, as well as an author and recognized subject matter expert in AI and Business Intelligence Leadership.

Stirrup’s keynote addresses are based on her two decades plus years of global experience and dedication to providing data strategy and business-focused solutions. In her address, Stirrup speaks on Data Mesh and Data Fabric, parsing out these terms and exploring them as they relate to Data Vaults, as well as the possibility of employing Data Vault modeling to solve real-life business challenges and deliver AI solutions. She also discusses whether Data Fabric and Data Mesh are simply fashionable terms, or whether they can be part of the overall weave of solving AI-focused business challenges.

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Speaker: Cynthia Meyersohn

Theme: Innovations on Data Vault 2.0

  • Areas of DV2 Coverage:
  • Model
  • Methodology
  • Architecture
  • Implementation
  • Standards
  • Best Practices
  • Ways of Working and Agility
  • Physical Design

Data Vault 2.0 is a holistic solution that enables prescribed methods to an age-old problem - getting value out of business data assets by releasing workforce innovation through managed self-service analytics capabilities. In the past few years, a new buzz word has gotten our industry's head spinning again - say hello to the Data Mesh.

Data Mesh was introduced to our industry through the magical story about a fictitious company named Daff Inc. In this story, Daff is the victim of so-called antiquated, monolithic approaches to data warehousing at a time when the business is crying to break the chains of IT constraints and open up the world of endless Artificial Intelligence and Machine Learning initiatives that move Daff into the new millennium of progressive analysis and frees Daff's workforce to create innovative data products that transform Daff from a iron-clad moth into a delicate, agile butterfly.

While the story is compelling, the reader is left to their own devices to understand exactly how they are going to arrive at this utopian destination.

Join me as I unravel the missing pieces and help you understand the "How To" needed to draw your company's roadmap to the "Boots on the Ground" possession of this utopian land.

Together, let's journey to the destination in reality.

Topics Covered:
  • The Reality of the Data Vault Methodology
  • The Theory and Concepts of Data Mesh
  • Aligning Reality with Theory
  • Building Your Roadmap Executing to the End State

Speaker: Kamil Piotrowski

The dispute over how to join the worlds of Business and IT so they can speak the same language, thus achieve common goals, is a never-ending story. In its roots it is a multi-factor problem that touches people’s education and experience in regards to business processes and technical aspects of an IT solution.

The universal truth is that each complexity can get divided into smaller pieces and then confronted again. Another is that people need to specialize because nobody can do everything. These both are actually great examples of “divide and conquer” approach and are perfectly utilized in Data Mesh in company with Data Vault 2.0.

The session presents what ways of working are to succeed in Data Vault 2.0 application that reflects Data Mesh principles.

Bringing together the learnings from one of the biggest and most recognizable projects in Roche IT, the author explains the end-to-end Data Product creation process, how independent scalable teams are established and what good and bad practices a principal should get to know to avoid project pitfalls.

The Framework (process, team organization and leadership) successfully creates bridges upon intersection parts of project’s components.

Thanks to this the Business-IT confusion gets significantly reduced, the value is brought faster and meets expectations.

Data architecture-as-a-service or DaaS is a new self-service paradigm that empowers local data owners to create architecturally compliant data repositories, domains, and pipelines without IT assistance. It is the culmination of self-service, where business units liberate themselves almost entirely from enterprise IT. If done right, DaaS reduces data bottlenecks, eases the burden on enterprise data teams, and empowers local domains to service their own data needs. It’s also a key ingredient in the data mesh, an emerging distributed architecture for data ownership and management.

Data architecture-as-a-service is a verbal twist on cloud processing environments, such as software-as-a-service or platform-as-a-service. This moniker conveys that it’s possible to abstract architecture and build it into easy-to-use, customer-facing tools. When we abstract data architecture, we solve the most enduring data pain point in the data world: the proliferation of data silos and pipelines that wreak havoc on data consistency and trustworthiness.

Major Topics Covered
• data architecture
• self-service
• data pipelines
• data mesh

• Data pain points
• Evolution of self-service
• Data Architecture as a Service - What it means
• DaaS - What it solves
• DaaS - How it works

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