Big Data needs data scientists, because at the moment, the meaning of all the attributes in the many big data, datasets that they consume, is in their heads. Further, there aren't many people who understand a domain well and can use the Big Data toolkits.
Despite the catchy title, schema-less databases benefit from a schema, as long as it is not like a traditional schema that gets in the way as much as it helps. This talk introduces Semantic Technology for Big Data Scientists and NOSQL practitioners. What the attendee will learn:
- Very briefly what semantic technology is and how it works
- How, with a demonstration, semantic attribution can be added to datasets
- How semantic categorization can make building a big data metadata repository possible
- How the RDF triplestore in semantic technology, extends the notion of a graph database to one interoperable at webscale
- How Semantics promotes "schema-later" rather than "schema-less" where schema can be applied after the data has been harvested and analyzed, without requiring data conversion.
Big Data and NOSQL can be greatly enhanced by applying a little bit of semantics.