DQOps
DQLabs.ai
Collibra
Melissa Data Quality
Metaplane
RingLead
InfoSphere
Pimcore
Iteratively
Census
Segment
Metaplane
Fresh Paint
Telmai
Keen
Segment Protocols
DQOps is an open-source data quality platform designed for data quality and data engineering teams that makes data quality visible to business sponsors.
The platform provides an efficient user interface to quickly add data sources, configure data quality checks, and manage issues. DQOps comes with over 150 built-in data quality checks, but you can also design custom checks to detect any business-relevant data quality issues. The platform supports incremental data quality monitoring to support analyzing data quality of very big tables. Track data quality KPI scores using our built-in or custom dashboards to show progress in improving data quality to business sponsors.
DQOps is DevOps-friendly, allowing you to define data quality definitions in YAML files stored in Git, run data quality checks directly from your data pipelines, or automate any action with a Python Client. DQOps works locally or as a SaaS platform.
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DQLabs.ai - The Modern Data Quality Platform.
Census - the #1 Reverse ETL tool for data teams
Collibra - Collibra automates data management processes by providing business-focused applications where collaboration and ease-of-use come first.
Segment - We make customer data simple.
Melissa Data Quality - Melissa helps companies to harness Big Data, legacy data, and people data (names, addresses, phone numbers, and emails).
Metaplane - Metaplane is the Datadog for Data — a data observability tool that continuously monitors your data stack, alerts you when something goes wrong, and provides relevant metadata to help you debug.