Trends in Data Science

Ten Trends in Data Science 2015 | Kurt Cagle | LinkedIn

1. "Data Virtualization: data can come in from multiple channels and formats
2. Hybrid Data Stores: XML, JSON, RDF and relational data in a single system
3. Semantics Becomes Standard: SPARQL 1.1
4. Hadoop Without Map-Reduce and Map-Reduce Without Hadoop
5. Databases Become Working Memory
6. Universal Data Query Language
7. Data Analytics Moves Beyond SQL
8. JavaScript Stack Solidifies
9. Data Science Teams
10. Data Visualization and Flexible Reporting"