Company
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June 2, 2022

Bigeye completes the SOC 2 Type 2 examination

We’re thrilled to announce that Bigeye has successfully completed the 2022 Service Organization Control (SOC) 2 Type 2 examination for Security, Availability, and Confidentiality.

Bigeye Staff

We’re thrilled to announce that Bigeye has successfully completed the 2022 Service Organization Control (SOC) 2 Type 2 examination for Security, Availability, and Confidentiality. The examination was performed by a leading independent service auditor for which Bigeye received an objective evaluation on our system and the suitability of the design and operating effectiveness that address compliance and operations.

The SOC 2 security report can be issued for one or more categories (security, availability, processing integrity, confidentiality or privacy). Type 2 specifically addresses an organization’s principal service commitments and system requirements based on applicable trust services criteria.

Kyle Kirwin, Bigeye’s CEO, says: “Our customers trust Bigeye for data observability on their most sensitive data, requiring us to maintain the highest levels of compliance and security. Completing our SOC 2 Type 2 evaluation for security, availability, and confidentiality underscores the commitment we’ve had to defending the security posture of our customers since day one.”

Bigeye is committed to performing the SOC 2 Type 2 evaluation for years to come, as we invest in best-in-class safety measures to deliver enterprise-grade, secure and compliant solutions to all of our customers.

Learn more about data observability today.

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Resource
Monthly cost ($)
Number of resources
Time (months)
Total cost ($)
Software/Data engineer
$15,000
3
12
$540,000
Data analyst
$12,000
2
6
$144,000
Business analyst
$10,000
1
3
$30,000
Data/product manager
$20,000
2
6
$240,000
Total cost
$954,000
Role
Goals
Common needs
Data engineers
Overall data flow. Data is fresh and operating at full volume. Jobs are always running, so data outages don't impact downstream systems.
Freshness + volume
Monitoring
Schema change detection
Lineage monitoring
Data scientists
Specific datasets in great detail. Looking for outliers, duplication, and other—sometimes subtle—issues that could affect their analysis or machine learning models.
Freshness monitoringCompleteness monitoringDuplicate detectionOutlier detectionDistribution shift detectionDimensional slicing and dicing
Analytics engineers
Rapidly testing the changes they’re making within the data model. Move fast and not break things—without spending hours writing tons of pipeline tests.
Lineage monitoringETL blue/green testing
Business intelligence analysts
The business impact of data. Understand where they should spend their time digging in, and when they have a red herring caused by a data pipeline problem.
Integration with analytics toolsAnomaly detectionCustom business metricsDimensional slicing and dicing
Other stakeholders
Data reliability. Customers and stakeholders don’t want data issues to bog them down, delay deadlines, or provide inaccurate information.
Integration with analytics toolsReporting and insights

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