Data Mesh

A decentralized framework to manage data as products

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A domain-oriented data ownership and architecture, to increase the agility and responsiveness of data teams

Centralized and monolithic data platforms are often characterized by a lack of agility, scalability, and flexibility, which can lead to data silos, slow innovation cycles, and high maintenance costs. Data mesh enables data-driven organizations to scale and innovate by applying distributed domain-driven design, product thinking, and self-serve platform design to data. Data mesh also empowers domain teams to own and share their data as products. Sigmoid can assist you in implementing data mesh by applying the principles of data engineering, data strategy and cloud data warehouse to unlock the full potential of enterprise data with robust governance.

Core components of a data mesh

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Data as a product strategy

Apply product philosophy and design thinking to improve the quality, usability, and scalability of data.

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Domain-driven data ownership

Organize analytical and operational data based on domains, allowing each team to be accountable for their own data.

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Self-service data infrastructure

Enable creation of domain-agnostic functionality, tools, and systems to create, implement, and manage data products for all domains.

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Unified governance

Automate the data governance system and make sure that all data products can work together effectively across domains.

Customer success stories

Successfully implementing a data mesh helps enterprises monetize their data products

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Identify the critical domains

Pay immediate attention to critical domains that generate the highest revenue or have the most significant impact on the business.

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Build specialized data hubs

Start with creating a domain-specific data hub to collect, process and analyze data from various sources and then scale it across all domains.

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Assign domain ownership

Allocate a dedicated domain owner to each data hub who will own the decisions regarding data quality, access, and usage.

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Expand to other domains

Scale your data hub across other domains while updating data contracts for the new domains to maintain consistency across the mesh.

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Improve and scale continuously

Review and refine the architecture of the data hubs periodically to ensure it meets the evolving needs of the organization.

Data mesh is a decentralized data architecture that organizes data by a specific business domain, for example, marketing, sales, customer service, and more—providing greater ownership to the producers of a given dataset.

Implementing data mesh offers various advantages, including greater data independence, quicker decision-making, accelerated value delivery for data projects, improved scalability, minimized data isolation, and enhanced collaboration across different functions.

In a data lake architecture, the data team controls all pipelines, whereas in a data mesh architecture, domain owners directly manage their respective pipelines.

A data contract is a formal agreement between users of a source system and the data engineering team responsible for extracting data for a data pipeline. This data is then stored in a data repository, such as a data warehouse.

Both data mesh and data fabric offer data architectures that facilitate an integrated and connected data experience within a distributed and complex data landscape. Both approaches focus on delivering data products. However, data mesh emphasizes product thinking as a fundamental design principle for data.

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