Data Integration revolves around the ability to handle all types of data. However, some of the most important data we deal with might not be what you'd expect. In a quest to build more efficient processes, one of our top priorities today is to create and consume rich and powerful metadata, which is basically “data about data.” While many people might know its definition, not everyone understands its value. There are five main types of metadata: business, structural, navigational, analytical, and operational. Each plays a large part in the building of data integration components. While each of these types of metadata may be created and managed in a different tool, the true benefit is in our ability to share the data. At the center of all this metadata is data integration and our desire to interface with all of it.Source system data can be examined to understand relationships and business definitions assigned at the entity and field level, so that analysts know the exact business purpose of each piece of data being mapped. By pulling in the physical data structures, developers can understand how the data is physically being stored. Navigational metadata can then be generated so downstream users know the data’s lineage — or simply: where the data was sourced from and the transformations that were applied along the way. Analytical metadata is used to streamline the creation and management of business intelligence (BI) reporting. The operational metadata generated and captured about each data integration process allows operations teams to fully understand the health of the system and in the event an error occurs, pinpoint any issues.
All of this metadata can easily be shared across several groups and, more importantly, several applications. At Merkle, we in fact are able to leverage prebuilt and custom-made metadata “bridges” enabling the movement of metadata seamlessly among applications. This facilitates the movement of data across key components, such as customer data integration (CDI), campaign management and BI systems, to enable us to build robust solutions for our clients.
Without the ability to share metadata we’d lose time and efficiency by introducing an error-prone process to separately manage this information in every program.
Our ability to not only process our clients’ business data, but also the metadata that revolves around it, is what allows us to build enterprise solutions for our clients. To learn more about Merkle’s Data Management Cloud offering, visit our product page.