Monte Carlo: Establishing Trust through Data Observability

Data observability refers to the ability to collect, measure, and analyse data from various sources in order to understand the current state and behaviour of a system.This includes monitoring the system's performance, availability, and errors, as well as identifying patterns and anomalies in the data. By implementing data observability, organisations can gain insights into their systems and make data-driven decisions to improve performance, optimize resources, and reduce costs. Common tools used for data observability include logging, metrics, tracing, and alerting. In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Lior Gavish, Co-Founder and CTO at Monte Carlo, to discuss:Getting started with data observabilityObservability trends for 2023How to implement and common challenges

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Making the most out of your data can feel overwhelming. Not only do many businesses have more data than they know what to do with, but they also often struggle to gain insights from some of the most valuable data in their possession, leading to many of their crucial data assets going unused. Whether it's issues with data quality, visualization, or management, getting lost in the sea of enterprise data at your possession can make it impossible to make smart, data-driven decisions that improve your business. The "Don't Panic! It's Just Data" podcast delves deep into the power of enterprise data. From groundbreaking vendor solutions to expert-backed best practices for making the most of your data assets, join us as we gather insights from leading tech vendors and professionals who depend on data daily.