AI TOOL PROFILE
decube: Data Context and Governance Platform
- Data and Analytics
- Data Governance
- Mid-market companies
- Enterprise companies
- Data engineering teams
- AI/ML engineers
- Data governance leads
Pricing
The Starter plan is $175/user/month (minimum 10 users) and the Growth plan is $225/user/month (minimum 20 users). Additional monitors cost $0.59 each and additional data sources cost $100/month. All plans are billed annually.
At a glance
- Best for
- Mid-market companies, Enterprise companies, Data engineering teams, AI/ML engineers, Data governance leads
- Key use cases
- Pipeline Monitoring, Root-Cause Analysis, Data Governance Compliance, AI Model Data Validation, Data Reconciliation
- Integrations
- Snowflake, Amazon Redshift, Google BigQuery, PostgreSQL, MySQL
- Official website
- Visit decube official website
How AI is used
decube is a data context platform designed to unify observability, discovery, and governance. It provides tools for monitoring data pipelines and managing metadata, which may help organizations maintain data integrity for decision-making and compliance.
The software is designed for data engineers, AI/ML engineers, and product teams. It helps these users track data flow and identify anomalies before they impact downstream reports or AI models.
Key capabilities include ML-powered anomaly detection, column-level lineage for root-cause analysis, and a no-code configuration for data quality metrics. It also includes an AI assistant named Trusty that supports metadata curation and SQL conversion.
Buyers should confirm the minimum user requirements for the Starter and Growth plans and verify if their specific data sources are supported by the available connectors.
Key Features
Data Observability
Uses ML-powered anomaly detection to identify schema changes, duplicates, and null values in data pipelines.
Column-Level Lineage
Maps data flow from source to target to support root-cause analysis of data issues.
Metadata Management
Provides a data catalog and business glossary to help teams organize and discover data assets.
Data Governance
Supports automated policy management for tagging and classifying assets, including PII and GDPR labels.
Trusty AI Assistant
An AI companion that supports Text2SQL conversion and provides automated data quality suggestions.
No-Code Quality Configuration
Allows users to set up monitors for volume, nulls, and duplicates without writing code, while supporting custom SQL tests.
Use Cases
Pipeline Monitoring
Detecting schema drifts, duplicates, and nulls to support pipeline reliability.
Root-Cause Analysis
Using column-level lineage to trace data issues back to the source and evaluate downstream impact.
Data Governance Compliance
Applying classification policies to protect sensitive data and support HIPAA or GDPR compliance.
AI Model Data Validation
Gaining visibility into the data feeding into AI/ML models to support model accuracy.
Data Reconciliation
Comparing differences between staging and production tables using data-diff tools.
Integrations
- Snowflake
- Amazon Redshift
- Google BigQuery
- PostgreSQL
- MySQL
- Databricks
- Tableau
- Power BI
- dbt
- Apache Airflow
- Azure Synapse
- AWS Glue
- Azure Data Factory
- Slack
- Microsoft Teams
- Jira
FAQ
What is decube used for?
- decube is used to monitor data quality, manage metadata, and govern data assets through observability tools and automated lineage mapping.
Who is decube designed for?
- It is designed for Data Engineers, AI/ML Engineers, and Product teams at mid-market and enterprise-scale companies.
How does decube handle data security?
- The platform is SOC 2 Type II, ISO 27001, HIPAA, and GDPR compliant, using TLS encryption in motion and AES-256 encryption at rest.
What are the pricing tiers for decube?
- decube offers a Starter plan starting at $175/user/month with a 10-user minimum and a Growth plan at $225/user/month with a 20-user minimum.
Source category: Data & Analytics
Source subcategory: Data Governance
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