Recommendations*
Get smart suggestions, automating the next best tasks in Lightup to optimize your Data Quality coverage.
*Beta release
Recommendations*
Lightup Recommendations provide smart suggestions, automating the next best tasks to optimize your Data Quality coverage.
*Beta release
Automated Data Quality Recommendations
Recommendations are intelligent, contextual suggestions generated by Lightup, bringing more automation, intelligence, and efficiency to how data teams to optimize Data Quality across the enterprise by:
- Identifying gaps in Data Quality coverage.
- Prioritizing activation of metrics, monitors, profiles, etc.
- Automating setup and fine-tuning of checks, profiles, monitors, Anomaly Detection, and more.
Instead of manually auditing datasets, Lightup constantly scans your environment, usage patterns, and configurations to surface the most impactful actions.
How It Works
By continuously learning from usage patterns in Lightup,
every recommended action is prioritized by relevance and impact to optimize Data Quality and improve efficiency.
Scan
Lightup evaluates your current configurations and usage patterns.
Analyze
Lightup identifies gaps, patterns, and improvement opportunities.
Prioritize
Lightup prioritizes actions to optimize your environment.
Activate or Ignore
Activate or ignore with one click, Lightup takes it from there.
Maximize the value of every Lightup action — without manual audits and time-consuming processes.
Key Benefits
Accelerate Data Observability
Identify key assets with missing metrics, monitors, and settings that need attention.
Increase Efficiency
Skip manual audits and address what matters most, automatically.
Optimize Performance
Fine-tune configurations and activations for desired results.
Prioritize Tasks
Automatically get prioritized next-best tasks based on actual usage and importance to your team.
Join Exclusive Beta Preview
Be among the first to see how Recommendations work and help shape the future of Lightup by joining the exclusive beta preview, by invitation only.