SYNQ

Enhance data quality management with AI-driven monitoring and unified observability to streamline issue resolution.

Empowers teams to create, monitor, and manage reliable data products effectively.

Proactively catch data quality issues before they impact decision-making.

Empower data owners to ensure accountability and responsiveness to data quality issues.

Streamline incident handling to minimize data disruptions and enhance operational efficiency.

Streamline your incident management process to quickly resolve data issues and minimize impact.

Seamlessly link your data tools and workflows with SYNQ's integrations.

Gain insights into data incidents and performance metrics for improved reliability and cost management.

Capabilities to continuously detect, monitor, and alert on anomalies, freshness, volume, schema changes, and end-to-end lineage across data pipelines and assets.

Products: Anomaly Monitoring, Integrations, Quality, Cost, Usage & Performance Analytics

Capabilities for proactive, AI-driven monitoring, testing, triage, and resolution of data quality issues across datasets, metrics, and pipelines.

Products: Data Quality Management Suite, Anomaly Monitoring, Issue Resolution

Capabilities that triage incidents, assess impact, track status, coordinate remediation, and integrate with external ticketing and alerting systems.

Products: Incident Management, Issue Resolution, Data Quality Management Suite

Capabilities to create, track, and monitor datasets, metrics, APIs, and dashboards with dependency tracking, SLAs, health views, and ownership for reliable consumption.

Products: Data Products, Quality, Cost, Usage & Performance Analytics, Ownership Activation

Capabilities to assign and surface clear ownership, enforce SLAs and accountability, and provide governance-driven collaboration and visibility across data assets.

Products: Ownership Activation, Data Products, Data Quality Management Suite

Data Quality Management Suite

A comprehensive suite for AI-powered data quality management across pipelines. This solution integrates Data Quality MCP and Scout to enable teams to proactively manage data quality, identify issues early, coordinate remediation, and monitor data incidents effectively. It facilitates efficient workflows and enhances data reliability, ensuring high standards are maintained.

• Detect Issues Early
  Utilize AI to monitor data streams actively, ensuring prompt identification of discrepancies before they escalate.
• Automate Incident Triage
  Quickly triages and resolves data issues in real-time, significantly reducing time-to-resolution and operational overhead.
• Manage Quality Efficiently
  Centralize control over quality metrics across various data assets to maintain consistently high standards.
• Recommend Relevant Tests
  Automatically suggests tailored tests and monitors based on past issues and data context to improve overall data quality.
• Streamline Incident Management
  Facilitate quicker response through a comprehensive view of data health and ownership responsibilities.

Data Products

Platform to create reliable data products—datasets, metrics, APIs, dashboards; supports ownership, monitoring, and SLA tracking, and tracks dependencies to show health across assets.

• Facilitates Data Product Creation
  Enables teams to produce a variety of usable data assets designed around business needs.
• Tracks Data Dependencies
  Automatically monitors all dependencies, ensuring accurate updates and alerts for affected products.
• Offers Health Status Overview
  Gives teams real-time insights into the operational status of data products and their dependencies.
• Supports Ownership Management
  Clarifies accountability for data quality and ensures adherence to service levels.
• Enables Seamless Integration
  Facilitates smooth interactions with other platforms for enhanced data flow and reliability.

Anomaly Monitoring

AI-powered anomaly monitoring for data pipelines, detecting issues in freshness, volume, and schema changes across assets.

• Ensure Data Timeliness
  Regularly track and validate data freshness and volume to maintain data quality.
• Notify Teams Instantly
  Receive prompt alerts about anomalies, ensuring quick response and coordination.
• Identify Structural Changes
  Automatically recognize schema modifications to prevent data inconsistencies.
• Streamline Monitor Setup
  Effortlessly apply anomaly monitors to a wide range of data assets, enhancing coverage.
• Adapt to Business Dynamics
  Leverage adaptive monitoring that evolves alongside data patterns for better anomaly detection.
• Enhance Understanding of Data Flow
  Gain insights into data transformations and dependencies to improve incident management.

Ownership Activation

Module to assign data ownership and ensure accountability across data assets.

• Assign Data Owners
  This feature allows stakeholders to take responsibility for specific data assets, ensuring accountability and proactive management of data quality.
• Enhance Transparency
  Provides stakeholders a clear overview of who is responsible for each data asset, enabling informed actions during data quality incidents.
• Notify Relevant Owners
  Automatically routes alerts about data issues to the appropriate stakeholders, facilitating faster responses and reducing on-call burdens for data engineers.

Incident Management

AI-assisted incident management for data pipelines: triage, impact assessment, status tracking, and integration with external workflows.

• Assess Impact Quickly
  Efficiently identify and assess the impact of incidents on data products and services, allowing for rapid response.
• Connect With Essential Tools
  Enhance your incident management workflow by integrating with popular tools to streamline communications and ticketing.
• Maintain Clear Records
  Ensure all incidents are well-documented, improving future responses and team accountability.
• Simplify Incident Handling
  View all relevant incident details in one place to improve coordination and reduce response times.
• Streamline Decision-Making
  Quickly gain insights into affected data products and services, facilitating faster resolution times.

Issue Resolution

End-to-end workflow to resolve data issues: from detection to resolution, with root-cause analysis and cross-team collaboration.

• Streamline Workflow
  This holistic approach ensures that all aspects of issue management are interconnected, enabling teams to respond efficiently and effectively to data quality challenges.
• Identify Causes
  This capability allows teams to understand the root cause of issues quickly, facilitating faster resolution and preventing future incidents.
• Enhance Collaboration
  This feature ensures that the right stakeholders are engaged in the resolution process, leading to more informed and effective problem-solving.
• Assess Impact Automatically
  This feature provides instant insights into which critical data products are affected, helping prioritize resolution efforts according to business impact.

Integrations

Platform to connect with tools across the data stack; connectors to dbt Core/Cloud, Airflow, Looker, Tableau, Omni, Snowflake, BigQuery, Redshift, ClickHouse, Databricks and more.

• Monitor Data Warehouses
  Keep tabs on data freshness and anomalies across major data warehouse platforms.
• Leverage dbt Assets Easily
  Automatically expose models, tests, and sources from dbt, ensuring streamlined data quality management.
• Map BI Dashboards Effectively
  Ensure accurate lineage mapping from BI tools back to your data sources for better insights.
• Synchronize Tasks Seamlessly
  Integrate your Airflow tasks to improve orchestration health and performance.
• Enhance Data Collaboration
  Integrate various tools to create a holistic view of your data ecosystem.

Quality, Cost, Usage & Performance Analytics

Analytics product providing overview of incidents, SLAs, data usage, and cost; helps monitor data assets performance.

• Tracks SLA Compliance
  Ensures visibility into incident management and compliance with SLAs, allowing teams to respond proactively to data quality issues.
• Optimizes Data Costs
  Helps identify cost drivers in data usage, enabling teams to optimize expenditures and resource allocation.
• Improves Data Pipeline Efficiency
  Monitors runtime and efficiency of data processes, revealing areas for performance improvements and enhancing overall data reliability.
• Enhances Data Ecosystem
  Allows for easy integration with various data tools, facilitating comprehensive monitoring and observability across platforms.