Stop treating tables as raw storage dumps. DynaDatum DATSIS Studio operationalizes the 6 foundational Data Mesh principles to package, certify, and contract your Databricks Lakehouse assets.
Every data product generated by DynaDatum automatically satisfies these six verifiable enterprise criteria.
Generates rich domain metadata, business ownership definitions, and automated Unity Catalog tagging so consumers can find data products instantly in their enterprise catalog.
Binds every data product to a stable, programmatic 3-level namespace (catalog.domain_schema.product_v1) that never breaks downstream dashboards when underlying tables are refactored.
Embeds automated Delta Live Tables expectations (@dlt.expect_or_drop), schema anomaly safeguards, and freshness SLO contracts into the product definition before deployment.
Includes complete column descriptions, semantic data types, business rules, and sample SQL queries so consumers can self-serve without opening a ticket with data engineering.
Exports standardized Open Data Contract Standard (ODCS contract.yaml) and enables Apache Iceberg UniForm so data products can be queried seamlessly across engines.
Attaches Unity Catalog dynamic column masking, row-level security (RLS), and RBAC grant policies directly to the data product container before it lands in production.
DynaDatum compiles visual models directly into production Open Data Contracts and Delta Live Tables pipelines.
dataContractSpecification: 3.0.0
id: urn:datacontract:customer_analytics_product
info:
title: Customer 360 Analytics Data Product
version: 1.0.0
owner: billing_analytics_domain
status: active
servers:
databricks:
type: databricks
host: dbc-xxxx.cloud.databricks.com
catalog: main
schema: analytics
models:
customer_orders:
type: table
description: Certified customer spend aggregates
fields:
customer_id:
type: string
required: true
unique: true
email:
type: string
classification: pii
mask: mask_hash_sha256
total_spent:
type: decimal(18,2)
serviceLevelAgreement:
freshness: 1h
frequency: streaming