Summary Raiko Limmart, CEO and co-founder of LiTech (https://LiTech.app for a prolonged demo, mention Uncle Data!), discusses the importance of data observability and its challenges. He shares his journey into data quality assurance and explains the components of data observability, including data validation, profiling, and cataloguing. Raiko highlights the need for companies to start early with data observability and offers insights into LiTech's services, which automate data validation, detect anomalies, and provide insights on data quality. He also discusses the role of machine learning and AI in data observability and emphasizes the importance of establishing a data culture within organizations. Takeaways Start early with data observability to ensure accurate and reliable analytics and decision-making. Data observability is a collaborative process that requires the proper tooling, defined processes, and a data-driven mindset. LiTech offers a user-friendly data observability solution that automates data validation, detects anomalies, and provides insights on data quality. Companies should prioritize data literacy and SQL skills to implement data observability effectively. Establishing a data culture and involving the data team in decision-making is crucial for successful data observability implementation.