How do you monitor and troubleshoot data marts and data lakes for data issues, errors, and anomalies?
Data marts and data lakes are two common types of data repositories that serve different purposes and audiences in dimensional modeling. Data marts are subsets of data warehouses that are tailored for specific business units or analytical needs, while data lakes are large-scale storage systems that store raw and unstructured data from various sources. In this article, you will learn about the main differences, advantages, and challenges of data marts and data lakes, and how to monitor and troubleshoot them for data issues, errors, and anomalies.