Agile, distributed data teams and robust data governance policies are often seen as opposing forces, yet, they contribute equally to scaling data democratization and generating value. At NIBC, we leverage the features of modern data tools to enable a Hub-and-Spoke model while adhering to advanced data management strategies. We do that by implemeting a knowledge graph based data management framework, and leveraging metadata. A knowledge graph helps to capture the semantics and quality of your data and unravels the complexity of the data landscape. This enables you to make better-informed decisions about the use of data and the necessary (governance) actions. During this talk, we will explain what a knowledge graph for data management consists of and how to iteratively build it using a use case-driven approach. We will zoom in on a specific area of metadata and show how it is implemented using dbt.

Agile, distributed data teams and robust data governance policies are often seen as opposing forces, yet, they contribute equally to scaling data democratization and generating value. At NIBC, we leverage the features of modern data tools to enable a Hub-and-Spoke model while adhering to advanced data management strategies. We do that by implemeting a knowledge graph based data management framework, and leveraging metadata. A knowledge graph helps to capture the semantics and quality of your data and unravels the complexity of the data landscape. This enables you to make better-informed decisions about the use of data and the necessary (governance) actions. During this talk, we will explain what a knowledge graph for data management consists of and how to iteratively build it using a use case-driven approach. We will zoom in on a specific area of metadata and show how it is implemented using dbt.

Agile, distributed data teams and robust data governance policies are often seen as opposing forces, yet, they contribute equally to scaling data democratization and generating value. At NIBC, we leverage the features of modern data tools to enable a Hub-and-Spoke model while adhering to advanced data management strategies. We do that by implemeting a knowledge graph based data management framework, and leveraging metadata. A knowledge graph helps to capture the semantics and quality of your data and unravels the complexity of the data landscape. This enables you to make better-informed decisions about the use of data and the necessary (governance) actions. During this talk, we will explain what a knowledge graph for data management consists of and how to iteratively build it using a use case-driven approach. We will zoom in on a specific area of metadata and show how it is implemented using dbt.