My colleague Amir Halfon – MarkLogic’s CTO of Global Financial Services – just posted a new addition to his “Big Data Blog” describing how Financial Services organizations can benefit from Semantic Web Technology.
In the post, he lays out five different use cases – Customer 360, Data Provenance, Reference Data, Pre-Trade Analytics and Decision Support, and Compliance – and gives a high-level overview of the reasons why (and how) this type of non-relational technology is useful for each. Common to all the examples is the way Semantic Technology can help add meaning and context to data, without extensive human intervention, rigid data modeling, or costly ETL cycles.
If you’re interested in a quick introduction to uses of Semantic Web Technology, I recommend you check it out.
Like what you just read, here are a few more articles for you to check out or you can visit our blog overview page to see more.
A data platform lets you collect, process, analyze, and share data across systems of record, systems of engagement, and systems of insight.
We’re all drowning in data. Keeping up with our data – and our understanding of it – requires using tools in new ways to unify data, metadata, and meaning.
A knowledge graph – a metadata structure sitting on a machine somewhere – has very interesting potential, but can’t do very much by itself. How do we put it to work?
Don’t waste time stitching together components. MarkLogic combines the power of a multi-model database, search, and semantic AI technology in a single platform with mastering, metadata management, government-grade security and more.Request a Demo