Thought leadership
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November 22, 2024
The Future of Data Observability: Trends and Predictions for 2025 | Webinar
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Subscribe to the Data Leaders Digest for exclusive content on data reliability, observability, and leadership from top industry experts.
Get the Best of Data Leadership
Subscribe to the Data Leaders Digest for exclusive content on data reliability, observability, and leadership from top industry experts.
Stay Informed
Sign up for the Data Leaders Digest and get the latest trends, insights, and strategies in data management delivered straight to your inbox.
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Staying ahead of emerging trends and challenges is critical for data leaders. That’s why Bigeye’s leadership team is coming together to share their insights on what’s next for data observability in 2025.
Join us for a live webinar featuring Bigeye’s CEO, COO, and CTO as they reflect on last year’s predictions, reveal what surprised us, and forecast the future of data observability. From expanding observability to hybrid and legacy systems to the transformative power of automation, this session is packed with new insights for data leaders.
What you’ll learn:
- How enterprises will tackle observability challenges in hybrid and legacy systems.
- The role of automation in reducing alert fatigue and boosting efficiency.
- Broader market shifts shaping the future of data.
Details:
📅 Date: December 17th, 2024
⏰ Time: 2pm EST
Register here!
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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
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
Get the Best of Data Leadership
Subscribe to the Data Leaders Digest for exclusive content on data reliability, observability, and leadership from top industry experts.
Stay Informed
Sign up for the Data Leaders Digest and get the latest trends, insights, and strategies in data management delivered straight to your inbox.
Get Data Insights Delivered
Join hundreds of data professionals who subscribe to the Data Leaders Digest for actionable insights and expert advice.
