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June 17, 2022

Ventana Research names Bigeye as a finalist in Digital Innovation Awards

Bigeye is thrilled to announce that we have been selected as finalists in the 15th annual Ventana Research Digital Innovation Awards. These awards recognize the top technologies and products that demonstrate a striking impact in their respective markets.

Bigeye Staff

Bigeye is thrilled to announce that we have been selected as finalists in the 15th annual Ventana Research Digital Innovation Awards. These awards recognize the top technologies and products that demonstrate a striking impact in their respective markets.

This year's finalists represent a wave of technological advancements in usage of AI and ML tools and applications. Bigeye was nominated in the Data category, for technical vendors that best exemplify innovation in data and related technologies for supporting data and information management related needs. Other finalists in the same category include MongoDB and Astronomer.

The awards recognize achievements in technology across 10 separate verticals: Analytics, Data, Customer Experience, Digital Business, Digital Technology, Human Capital Management, Marketing, Office of Finance, Office of Revenue and Operations & Supply Chain. All 30 finalists, including Bigeye, are in the running for the overall Digital Innovation Award, which will be announced at a later date.

Ventana Research is a comprehensive market research and advisory firm with expertise spanning business and tech. Its Digital Innovation Award program launched in 2008, and each year the awards go to organizations that most successfully demonstrate an impact on people, processes, information and technology.

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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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