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Decentralized data architecture with autonomous and interconnected data domains.
In a data mesh architecture, domains allow you to define clear ownership by assigning domains to specific data owners and organize data by business areas to make it easier to discover and access relevant data assets.
Within domains, define data products that package curated information of multiple data assets, making it easier for users to access relevant data products and becomes a shared resource among teams for better collaboration.
Curate specific segments of your datasets to deliver the most relevant information to your data consumers. This avoids information overload and ensures data products are focused and deliver only the most valuable insights.
Define a single table in multiple ways within different data assets, ensuring each data product aligns to business logic. Assign clear aliases to table names and columns, providing valuable context for use.
Data contracts ensure data quality and trust are at a high-level between producers and data consumers.
Clear ownership, contracts, and quality, on the same governed foundation.
Give each team clear ownership of the data products they produce.
Package datasets as products others can find, trust, and reuse.
Producers promise shape, quality, and freshness so consumers can rely on it.
Every data product is watched for freshness, volume, and quality.
Consumers browse and request trusted data products in one place.
Every product links to its lineage, so consumers know where data comes from.
Give each team ownership of the data they know best, with clear boundaries.
Package datasets as products with contracts, quality monitors, and documentation.
Let consumers find, trust, and use published data products across the organization.
Build and publish data products on top of your warehouses, lakes, BI, and orchestration tools. And many more..
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Data products stay governed on a metadata-only architecture that meets regulated standards.
Safeguarding your information with industry-leading standards.
Ensuring your information is protected with the highest level of integrity.
Ensuring the confidentiality and integrity of your healthcare data.
Protecting personal data with robust privacy and security measures.
Your data is encrypted in motion with TLS and at rest with AES-256.
If any of these sound familiar, it is time to give every team data products they can own and trust.
Analysts keep rebuilding the same dataset because no one trusts the last version
Every new data request waits on a central data team
No one can say who owns a table, or whether it is safe to use
Consumers find out data broke only after a dashboard is already wrong
The same metric means different things in different reports
Teams keep copying data into spreadsheets because they cannot find a source they trust.
Built for organizations scaling data ownership beyond a central team, so each team can own, publish, and stand behind the data products it produces.
Let teams own and govern their data products for compliance.
Curated data products with a clear owner
Data contracts and SLAs on every product
Quality monitored before anyone relies on it
Discoverable across risk, finance, and compliance
Give risk, actuarial, and claims teams ownership of trusted data.
Owned data products for policy and claims data
Contracts that hold quality between producers and consumers
Freshness and field health checks on each product
Easy to find, safe to reuse across teams
Scale data ownership across many teams and systems.
Curated products from multi source data
A clear owner and SLA for each product
Quality monitored at scale
Discoverable across the whole business
Move from a central bottleneck to data products each team owns.
Data products owned by the team that knows the data
Contracts and SLAs that keep them trustworthy
Quality and lineage built in
One place to discover and reuse trusted data
Trusted by organizations operating under OJK, BNM, MAS, and APRA regulatory frameworks across APAC.
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A data product is a curated, owned, quality-monitored set of data published for other teams to use. Decube lets teams compose data products from metadata and quality checks, assign an owner, attach an SLA, and make them discoverable and trustworthy.
A data contract is an agreement between the team that produces data and the teams that consume it, covering schema, freshness, and quality. In Decube each contract is enforced with live monitors and tied to the data product and its lineage, so a broken promise is caught before it reaches consumers.
A dataset is raw. A data product is curated, owned, documented, quality-monitored, and discoverable, packaged so other teams can trust and reuse it without checking with you first.
Every data product is assigned an accountable owner, so responsibility for its quality, access, and documentation is always clear, and no critical data goes unowned.
A data marketplace is where people discover and request trusted, ready to use data products; a data catalog is the underlying inventory of all data assets. In Decube, data products are published from the same catalog, quality, and lineage foundation.
AI and agents are only as reliable as the data behind them. Owned, quality-monitored data products with contracts and lineage give your AI initiatives trusted, well-governed inputs, the same context layer Decube provides for Data-to-AI Governance.
Rated 4.6/5 on
Automation of Monitors
Data Lineage
Their data contract module is amazing which virtualises and runs monitors.
Big fan of their UI/UX, it simple but managing all the complex task.
My team uses on a daily basis.
Seamless integration with all the data connectors. We also liked the new dbt-core connector directly integrated with Object storage.
Automated Column-Level lineage
Perfect blend of Data Catalog and Data Observability modules.
Business users are able to understand if the reports /dashboard have issues / incidents.
Personally liked the monitors by segment since we have mulitple business it provides incidents breakdown by attributes.
UX and UI, features, flexibility and excellent customer service. People like Manoj Matharu took the time to understand my business and data needs before trying to solution.
One of the best-designed data products. Our complete data infra is getting observed and governed by decube. My fav is the lineage feature which showcases the complete data flow across the components.
What I appreciate most about Decube is its intuitive design and the way it supports maintaining data trust. The platform allows for straightforward monitoring of data quality, making it easier to detect issues early on.One of the most valuable aspects is the transparency it brings to our data pipelines, which also streamlines collaboration among teams. The greatest benefit is the assurance that our data remains accurate, consistent, and prepared for decision-making, all without the need to spend countless hours troubleshooting.
Decube is packaged of solution for us. We were struggling to find one good tool in which we can intigrated with our existing data stack we are using mysql. As a DevOps we used to write crond jobs to check data quality but when we adapt this tool the work and quality both are improved. I highly recommend !
Bring lineage, quality, governance, and AI together in one platform—so your teams and AI agents can act with confidence.
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