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View the content from our half-day virtual event that originally aired on Thursday, September 29 to learn how to take Data Mesh from theory to practice. A first-of-its-kind technology partner showcase, this forum is designed to provide an accelerated learning opportunity to help data leaders take their best next step on their data mesh journey.
Check out the agenda below!
Did you know that treating data as a product could drive revenue? Learn all about the ROI of Data Mesh.
Learn how to leverage SQL-based MPP query engine for unlocking the value of distributed data and reducing the time-to-insight.
ETL, ELT, or maybe no L at all? Hear from your peers who’ve found a way to almost stop moving & copying data by giving teams access to data where it lives.
Organizations that are interested in data mesh, are also starting with figuring out “how do we build to scale?” Data mesh requires an organization change that requires buy-in by the business. Join this session to hear Teresa Tung, Accenture’s Cloud First Chief Technologist, describe how technology-led efforts can use initial highly-visible data products and existing projects to get started, to set the foundation to scale, and simply to get the broader organization to care.
Starburst enables organizations like Genus to unlock the value of distributed and complex data by providing a single point of secure data access. By treating data as a product, organizations manage data in a way that maximizes its value and leads to faster & better decisions.
In this session, Alison Huselid, SVP of Product and Vishal Singh, Head of Data Products at Starburst, will walk you through turning distributed data into consumable data products in a manner such that data consumers can effortlessly explore, discover, analyze, and share data across organizations. Patrice Linel, Sr Manager of Data Science & Data Engineering at Genus, will conclude the session by sharing a practical use case of innovating with Starburst and data mesh.
The Lake House Architecture is ideally suited to help teams build data domains, and using the data mesh approach to bring domains together to enable data sharing and federation across business units. This approach can enable better autonomy and a faster pace of innovation, while building on top of a proven and well-understood architecture and technology stack, and ensuring high standards for data security and governance.
In this session, Antony Prasad Therajav at AWS will discuss the AWS Lake House Architecture, their Data Mesh journey, and how customers can store domain-specific data in a data lake and use a ring of purpose-built data services around the lake.
Federated computational governance is one of four key pillars of data mesh, describing data governance enforcement and automation. In this session, Zachary Friedman, Director of Product at Immuta, will explain an implementation of automated data access in data mesh, showcasing how a data access platform when paired with data products can help organizations ensure that the right people are authorized to access the right data.
Zachary will also discuss the limitations of a command-and-control, fully-centralized governance model, and show how a shared governance model can be applied to data security, programmatically.
Metadata is the key to unlocking value in your Data Mesh, but we all know it can be difficult for data teams to actually use it. Too often, it ends up unused in yet another siloed tool. In this session, Prukalpa Sankar, Co-Founder at Atlan will discuss how modern metadata enables fundamental Data Mesh principles and what a purpose-built metadata platform for the Data Mesh should look like, including real-life examples of Data Mesh principles in action from companies like Cars.com.
Discover how Tableau enables a strong data fabric design allowing you to have a 360 view of your customer as part of your data mesh strategy. In this session, Chandrinka Shankarnaryan, VP of Product, will discuss how Tableau is critical to supporting your data analytics initiatives.
The idea of a Data Mesh is alluring; it combines business needs with technology in a way we don’t typically see. It promises a solution to help break down organizational barriers in extracting value from data. To do this, companies must adopt four principles of discoverability, accessibility, ownership, and (federated) governance, which require a coordinated effort across technical and business unit leadership. In practice, each group that owns a data domain across a decentralized organization may need to employ a hybrid group of data workers to take on the increased data curation, data management, data engineering, and data governance tasks required to own and maintain data products for that domain. Join this session with Firat Tekiner, Staff Product Manager in Data Analytics at Google Cloud, to learn you can achieve this by having federated computation and access layers while keeping your data in BigQuery and BigLake. In addition, Dataplex provides the ability to handle centralized administration and governance.
As you start your journey towards a data mesh ecosystem, typically some of the first things you need to consider are your operating model and technology landscape. While these are essential, an equal amount of importance needs to be placed on putting the right people and processes in place to make your vision a reality. Building this modern culture of data requires that you embrace and champion a mindset of experimentation and innovation within both the technology and business teams. To realize the maximum benefit of an organizational transformation like this, you need to take the opportunity to reimagine existing tools, methods, and business processes.
In this session, Kris Karaikudi, Director, Global Data Strategy and Sharjeel Khalid, Senior Delivery Principal, Global Data Strategy at Slalom will share their experiences and dive deeper into some of the key strategies you can leverage to realize your data mesh vision.
Cloud First Chief Technologist, Accenture
Director of Product, Immuta
Director, Global Data Strategy, Slalom
Senior Delivery Principal, Global Data Strategy, Slalom
VP of Product, Tableau
Senior Partner Solutions Architect, AWS
EMEA Data Analytics Solution Lead, Google
Sr Manager Data Science & Data Engineering, Genus PLC
SVP, Product, Starburst
Head of Data Products, Starburst
Up to $500 in usage credits included