Metadata-driven data pipelines are the secret behind seamless data flows, empowering data magicians to create adaptable, scalable, and evolving data management systems. Leveraging metadata, these pipelines are dynamic, flexible, and automated, allowing for easy handling of changing data sources, formats, and requirements without manual intervention.
Join Murray Robinson and Shane Gibson as they chat with Pawel Huryn about product management. What it is, and isn’t? How to motivate teams and what makes a product succeed. We discuss the difference between product management, which focuses on discovery and project management, which focuses on delivery. And how to do both at the same time in one empowered product team. We talk about how you can become a product manager and the best product management tools to use. Join us as we uncover valuable insights to help you succeed in this critical role.
Join Shane Gibson as he chats with Joe Reis on his experience in building and running a successful data and analytics consulting company.
Data modeling is a crucial process that involves creating shared understanding of data and its relationships. The three primary data model patterns are conceptual, logical, and physical. The conceptual data model provides a high-level overview of the data landscape, the logical data model delves deeper into data structures and relationships, and the physical data model translates the logical model into a database-specific schema. Understanding and effectively using these data models is essential for business analysts and data analysts, create efficient, well-organised data ecosystems.