An integrated data quality and governance platform

Meet the first data management platform to connect data quality, observability, and discovery. Get visibility into the health of your entire stack, and prevent data asset sprawl.

Trusted by data teams worldwide.

Reliably scale your team's compute costs

The only platform to give you visibility into pipeline metadata such as cost, query volume, and popularity. Monitor and optimize the health of your pipelines, processes, and data infrastructure as a whole.

Identify blindspots and never be caught off guard

Set thresholds and be alerted when queries, tables, or dashboards exceed their expected compute costs.

A full menu of monitors

Configure essential monitoring on schemas, tables, and columns. Choose from freshness, cardinality, uniqueness, and more.

Flexible and customizable to fit you

Automatically schedule and create thresholds with the ability to track the history of runs and visualize performance.

Understand the health of your data, pipelines, and infrastructure

Bring data observability into your catalog and keep a pulse on data quality. Set monitors and detect anomalies to prevent surprise bills.

End-to-end data quality monitoring

Secoda integrates with your entire stack to help detect issues all the way from data sources, across transformations, to BI layers. See data lineage across your entire infrastructure.

Prioritize the data that matters most

Identify the most popular tables and most used resources within your DAG. Automatically surface insights like which tables to deprecate or which resources require maintenance.

Know where your cost drivers are

Before getting stuck with an outsized bill, get insights into costly pipelines and assets where costs are created. Secoda will suggest methods to reduce and manage your compute costs.

Get alerts within your workflow

When a threshold is breached, notifications can be received via app, Slack, or email. Immediately see details like status and a list of resources related to the incident created from your DAG

"With Secoda, we can see all of our metadata in one place and build a single source of truth to enable self-serve analytics. These are huge time savings.”

Amit Jain

Technical Director, Data Systems

Upholding industry-leading security standards

SOC 2 compliant

Secoda is SOC 2 Type 1 and 2 compliant. The way we process and store client data is secure and protected, based on standards set by the AICPA.

Self-hosted environment

You can host Secoda in a self-hosted environment, behind your own VPN, and in your own VPC. Deploy via Terraform or Docker.

SAML, SSO, and MFA

Sign in with the services you already use, including Google and Microsoft SSO, Okta, MFA and SAML

SSH tunneling

Securely move data from your private databases to Secoda with SSH tunneling.

Auto PII tagging

Get control to remove or leave out sensitive datasets from your syncs or mark it automatically in Secoda.

Data encryption

Data managed with Secoda is fully encrypted in transit and at rest. We do not see the data we are moving.

FAQs

What is data monitoring and observability?

Data observability is a process and set of practices that aim to help data teams understand the overall health of the data in their organization's data systems. Data observability provides the context needed for organizations to proactively identify data errors, pipeline issues, and locate the source of inconsistencies to strengthen data quality over time. It allows enterprises to fix issues in complex data scenarios and identify situations before they have a huge impact on the business.

What is metadata monitoring?

The process of metadata monitoring typically involves collecting and analyzing metadata from sources across your organization, such as databases, data warehouses, data pipelines and more. With greater visibility into your metadata, you can better understand it and more easily search and find the data you need.

What are the top data monitoring and observability tools?

Data observability tools feature automated monitoring, root cause analysis, data lineage, and other features to proactively detect data issues. It is the ability to understand, diagnose, and manage data health across multiple IT tools throughout the data lifecycle.

What are the benefits of implementing data monitoring and observability?

The implementation of data observability and data monitoring offers several benefits, including improved data quality, more efficient data management, enhanced system reliability, and proactive issue identification.