Obtaining valuable insights faster from large, diverse data sets seems to be the primary goal in business. Unfortunately, the current options don’t work all that well — the data warehouse and conventional data lake, as well as Hadoop-based point solutions, all have their challenges. This interesting information came to us from the Smart Data Collective in their article, “The Benefits of Semantic-Based Data Modeling in the Smart Data Lake Era.”
Data modeling is most easily configured, structured and analyzed within the context of a smart data lake. You can create a single, semantic-based data model or enterprise knowledge graph for the entire organization.
Because smart data lakes leverage a semantic-based data model, the “meaning” of data with all the inherent, relationships and attributes can be easily captured and delivered.
Semantic data models also describe the data in your environment to give you better visibility into things like data provenance, creating an unbeatable combination of data management and analytics within a single application.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
