Big Data Glossary
What is Data Observability?
Definition of Data Observability
What is Data Observability?
Data Observability refers to the ability to monitor, measure, and understand the health, quality, and performance of data throughout its lifecycle. It involves tracking key metrics such as data accuracy, completeness, timeliness, and consistency to ensure that data is trustworthy and usable. Data observability tools help organizations detect anomalies, identify issues in data pipelines, and quickly troubleshoot any problems that may arise. By providing deep visibility into data processes, Data Observability enables businesses to maintain data integrity and ensure that analytics and decision-making are based on reliable information.
Introducing Crosser
The All-in-One Platform for Modern Integration
Crosser is a hybrid-first platform that in one Low-code platform has all the capabilities that you traditionally would need several systems for.
In one easy-to-use platform:
- Event Processing
- Data Ingestion & Integration
- Streaming ETL
- Batch ETL/ELT
- Reverse ETL - bidirectional
- Stream Analytics
- Functions & custom code (python, C#, JavaScript)
- Inference of AI/ML models
- Automation Workflows
Platform Overview
Crosser Solution for Data Mining
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- Save cloud cost
- Reduce use of critical resources
- Simplify your data stack
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