1. CS 540 Database Management Systems Current Trends in Database Research

2. Exiting Time for Database Research • Data, data is everywhere, everybody is generating it and using it. • It determines how we make decision. • “Looking for a career where your services will be in high demand? ... Provide a scarce, complementary service to something that is getting ubiquitous and cheap. So what’s ubiquitous and cheap? Data. And what is complementary to data? Analysis.” Hal Varian, UC Berkeley, Chief Economist @ Google

3. New Challenges in Databases Traditional RDBMS Functions Traditional Relational Data Traditional Users New Data/Info Management Functions? New Data Type? New Users?

4. Properties of New Data Sets • Traditional data sets • Large, homogenous, integrated, static • Web changed everything • Easy to publish and access data • Social network and Web 2.0 changed everything • Easy to share data for indusial • Novel scientific devices, sensor networks, … changed everything • Easy to create large data sets in a short period of time • New data sets • Big, heterogeneous, scattered, evolving

5. Ranking in DB Information Extraction Complex object indexing Stream data Data exploration and analytics Data integration New Types of Data • Text data • Multimedia data • Scientific data • Sensor data • Log data • Personal data • Social/network data • ... …

6. New Users • Everyone: scientists, financial/think tank/… analysts, health provides, normal users, … • Usability has become very important • Easy to use query interfaces, such as keyword queries • Efficient and Effective visualization techniques • Usable data-centric languages for developers.

7. New Hardware • Cheaper storage • Multicores and clusters • RAM is disk, CPU-cache is RAM • Novel buffer management, query processing and transaction management algorithms. • Rethinking the core engine: main memory databases

8. Selected Current Topics • Usable databases • Ranking in databases • Scalable social and graph data analysis • Information extraction, text databases • Data Integration • Stream Data Processing • Scalable machine learning • Database applications on crowd sourcing • …

9. Outlook • The database field will continue growing • External: growth of data/information • Internal: DB researchers are willing to broaden scope • Database researchers will meet many new friends (ML, IR, HCI, Network, SE, …) • Data analytics, information extraction, ranking, usable query interfaces, usable languages, unstructured data, …

10. Where to Look Further? • CS519 : Big Data Analytics and Exploration • Major DB conferences: SIGMOD/PODS, VLDB, ICDE, EDBT/ICDT. • Major DB journals: ACM TODS, IEEE TKDE, VLDBJ • Visionary: CIDR, Asilomar/ Claremont Report • Related communities • Information retrieval: SIGIR, CIKM • Data mining: KDD, ICDM • World Wide Web: WWW, WebDB