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Mizu: West Monroe’s Databricks Lakehouse Accelerator

Unlock insights with a scalable data platform

In today’s data-driven world, organizations face immense pressure to modernize and become more data-centric. However, navigating the complexities of modernizing data platforms and leveraging cloud technologies can be overwhelming.

That’s where Mizu, West Monroe’s Databricks Accelerator, comes in. Mizu simplifies the process of building a scalable, secure data platform, helping you unlock actionable insights quickly, whether you're on AWS or Azure. In just a few weeks, Mizu seamlessly integrates with your existing infrastructure, ensuring a smooth transition to a modern data environment.

How Mizu Works

Fast Data Ingestion

Mizu enables rapid ingestion of diverse data sources—whether files, databases, or APIs—into the Databricks lakehouse, delivering actionable insights in just days, not months.

Reusable Data Pipelines

With minimal configuration, Mizu creates reusable data pipelines that hydrate your lakehouse in hours, allowing for faster data access and decision-making.

Integrated Data Catalog

Mizu seamlessly integrates with the Databricks Unity Catalog, ensuring data cataloging and lineage from the start, while leveraging the latest Databricks features for enhanced functionality.

Scalable & Customizable

Built to scale, Mizu meets the largest data demands and is fully customizable, ensuring it adapts to your unique business needs and drives team efficiency.

Mizu’s Results & Impact

  • <3 weeks

    fully operational platform

  • <1 hour

    to ingest new data source

  • 800+ hours

    save months of developer hours

Mizu, West Monroe’s Lakehouse accelerator, automates common, repetitive data engineering tasks so data engineers and analysts can focus on constructing valuable business insights and analytics.

The Technology Behind Mizu

Mizu leverages the latest features of Azure, AWS, and Databricks, including Unity Catalog, to deliver best practices for quickly and securely scaling your data platform. It’s already implemented across industries for data warehousing, master data management, and machine learning/AI use cases.