The Rise of Data Downtime: Making Observability A Pillar of Your Data Lake

Unlock the secrets to reliable data with Bar Moses, CEO and co-founder of Monte Carlo, as he delves into the concept of data downtime and how software engineering best practices can help manage it. This insightful session from the Qubole Data Lake Summit will guide you through the crucial steps to enhance your data’s reliability, ensuring your enterprise can fully trust its data by minimizing data downtime.

What You’ll Learn:

Understanding Data Downtime:
- Learn what data downtime is and why it’s a critical issue affecting organizations across all industries.
The Importance of Data Observability:
- Discover the concept of data observability and its role in identifying, evaluating, and ensuring the quality of data in your systems.
Applying Software Engineering Best Practices:
- Explore how leveraging software engineering methodologies can provide solutions to manage and minimize data downtime effectively.
The Five Pillars of Data Observability:
- Understand the five key pillars necessary for achieving data observability: Freshness, Distribution, Volume, Schema, and Lineage.
Practical Tips for Implementing Data Observability:
- Gain actionable insights and practical tips to implement data observability within your data lake, enhancing data reliability and trust.
Measuring and Managing Data Downtime:
- Learn how to set SLAs and SLOs for your data, measure the number of data downtime incidents, and improve time to detection and resolution.
The Future of Data-Driven Decision Making:
- Embrace the shift towards a more data-driven approach, understanding the necessity of getting the fundamentals of data accuracy, integrity, and uptime right.

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