Today’s enterprise data platforms leave a universal set of challenges, including data silos, data governance, data quality, and data access. These challenges delay organizations from delivering data on time and creates friction between data consumers, data producers, and central IT teams.
Data mesh is a methodology that helps solve these challenges by decentralizing data ownership and management, creating data products, and establishing a culture of data collaboration. As a result, data consumers get faster access to data and central IT delivers data for governed self-service analytics.
Data Producers and Consumers Are Better Together Deliver Data. Build Trust.
"Dremio allows us to bring state-of-the-art tooling alongside self-service data access in a governed way...The reason Dremio was such a great fit is that it created a data mesh for us across all these areas and allowed our customers to use SQL to access and explore data across the enterprise. Our goal in this expanded data mesh is to make Dremio the single consistent query engine. It's not just about SQL-based querying, but also about supporting BI tools, point-and-click interfaces, and different ways in which users want to access the data in a common way.”
Deepika Duggirala
Senior Vice President, Global Technology Platforms | TransUnion
Dremio’s Unified Access Layer Allows Teams to Build and Share Data Products in A Single Place
Dremio is the only data lakehouse that delivers self-service data products anywhere, on-premises, hybrid, or cloud. Unify enterprise data and simplify data access with a single solution for data mesh. Here’s how we make the four core principles of data mesh a reality.
Self-Serve Data Platform
Answer business questions using SQL or an easy low-code/no-code experience and integrations for all data consumers. With data reflections, Dremio is the fastest for all BI workloads.
Give data consumers a consistent and accurate view of data at all times. With data as code, catch mistakes before deploying your ML models and BI dashboards into production.
Discover and understand data with minimal to no data engineering overhead. Federate domain ownership and enrich your data with business context using the searchable, integrated catalog experience.
Build trust between domains and make decisions about how data is used and shared across the enterprise. Govern access to data and remove the need for copying data into data warehouses or BI extracts.
In this episode, Nik Acheson (Sr. Director at Dremio) shares his first-hand experience leading digital transformations across enterprises such as Nike, Zendesk, and American Eagle. See a real-world demo of Dremio's semantic layer unifying data in Iceberg with Delta Lake and Snowflake, without any data movement or copies!
Simplifying Data Mesh with Dremio's Data Lakehouse
A playbook for simplifying data mesh for self-service analytics on Dremio's open data lakehouse. Learn the benefits of data mesh and navigating organizational adoption.
Data as code is the practice of managing data the same way software manages code in application development. Learn how Dremio Arctic simplifies and accelerate the process of building, managing, and sharing data products.