The business environment has become very dynamic, uncertain, and volatile. Many companies understand the role of data in getting a competitive advantage. Many business people declare that “data is their company’s asset,” and they need “to get value from it” by “becoming data-driven.” Many established and new data management capabilities should assist in reaching these goals. Knowledge graphs, metadata management, and data lineage are examples of these new capabilities that have been actively discussed and developed. There are some challenges associated with the implementation of these capabilities:
- Definitions of these capabilities are ambiguous and depend on the context.
- These capabilities intersect each other to a great extent and have many dependencies.
- Their implementation is time- and resource-consuming.
This series of articles aim to:
- Illustrate relationships between key concepts that form the core of these capabilities: data, metadata, information, and knowledge
- Analyze and compare knowledge graphs (KG), data lineage (DL), and metadata management (MM) by comparing:
- Definitions and structures of each capability
- Business drivers that motivate companies to establish them
- Architecture and technology
- Use cases
- Demonstrate differences and similarities between these three capabilities
Knowledge Graphs, Data Lineage, and Metadata Management: Introduction
The business environment has become very dynamic, uncertain, and volatile. Many companies understand the role of data in getting a competitive advantage. Many business people declare that "data is their company's asset," and they [...]
Knowledge Graphs, Data Lineage, and Metadata Management: Business Drivers
A company meets various challenges that drive it to develop advanced data management capabilities. I investigated multiple sources. Below, you will find a summary of business drivers for each capability. Metadata management (MM) Key [...]
Knowledge Graphs, Data Lineage, and Metadata Management: Architecture and Technology
Now, we will look at the similarities and differences in data architecture and technology required to realize these three capabilities. Metadata management (MM) We have previously discussed that metadata can be of various types. [...]
Knowledge Graphs, Data Lineage, and Metadata Management: Use Cases
The business drivers that we discussed earlier lead to the corresponding use cases. In some situations, business drivers and use cases are similar. Metadata management (MM) MM assists in performing the following business tasks: [...]
Knowledge Graphs, Data Lineage, and Metadata Management: Similarities and Differences
Metadata management (MM), knowledge graphs (KG), and data lineage (DL) are data management capabilities that have a lot of similarities and some differences. In any case, they intersect each other to a great extent, [...]
