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December 11, 2024

Introducing Bigeye’s Looker Connector: Lineage-Enabled Observability for Looker Workflows

Tracking lineage in BI tools can often be a complex and manual process. The Looker Connector changes that.

Adrianna Vidal
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We’re excited to announce the launch of Bigeye’s Looker Connector, a powerful new tool that brings column-level lineage to Looker environments. With this addition, Bigeye now helps data teams trace dependencies across Looker’s integration, semantic, and transformation layers, all the way through to its visualization outputs.

What Makes the Looker Connector Special?

Tracking lineage in BI tools can often be a complex and manual process. The Looker Connector changes that by automating lineage generation and offering visibility into how data moves and transforms within Looker. This includes:

  • Column-Level Lineage: See how data is transformed and flows through your Looker instance with unmatched granularity.
  • Comprehensive SQL Support: Parse custom SQL within Looker to track transformations, no matter how layered or complex.
  • Cross-Source Coverage: Tie together Looker’s data with the rest of your stack, including legacy systems like SSIS.

How It Works

Get started with Bigeye’s Looker Connector by simply adding your credentials and you’ll be on the way to mapping out lineage. It works across Looker’s integration and transformation layers (including semantic models and custom SQL) and provides clear, actionable insights into dependencies.

Why This Matters

Data teams rely on Looker for business-critical insights, but maintaining trust in those dashboards depends on knowing exactly how data is transformed and where it comes from. Bigeye’s Looker Connector simplifies this process by automating lineage generation, allowing teams to spend less time troubleshooting and more time delivering value.

Part of Your Enterprise Data Ecosystem

The Looker Connector builds on Bigeye’s established lineage capabilities for tools like Tableau and Power BI. Together, these integrations provide comprehensive coverage for enterprise data pipelines, spanning cloud, on-prem, and hybrid environments.

See It in Action

Curious how the Looker Connector can improve your workflows? Request a demo today to see how Bigeye brings clarity and trust to your data.

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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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