Enabling Real-Time Business Intelligence

1. Front Matter

   PDF

2. Queries over Unstructured Data: Probabilistic Methods to the Rescue

   • Sunita Sarawagi

   Pages 1-13

3. Federated Stream Processing Support for Real-Time Business Intelligence Applications

   • Irina Botan, Younggoo Cho, Roozbeh Derakhshan, Nihal Dindar, Laura Haas, Kihong Kim et al.

   Pages 14-31

4. VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans

   • Song Wang, Chetan Gupta, Abhay Mehta

   Pages 32-49

5. Ad-Hoc Queries over Document Collections – A Case Study

   • Alexander Löser, Steffen Lutter, Patrick Düssel, Volker Markl

   Pages 50-65

6. ASSET Queries: A Set-Oriented and Column-Wise Approach to Modern OLAP

   • Damianos Chatziantoniou, Yannis Sotiropoulos

   Pages 66-83

7. Evaluation of Load Scheduling Strategies for Real-Time Data Warehouse Environments

   • Maik Thiele, Wolfgang Lehner

   Pages 84-99

8. Near Real-Time Data Warehousing Using State-of-the-Art ETL Tools

   • Thomas Jörg, Stefan Dessloch

   Pages 100-117

9. Addressing BI Transactional Flows in the Real-Time Enterprise Using GoldenGate TDM

   • Alok Pareek

   Pages 118-141

10. Near Real–Time Call Detail Record ETL Flows

    • Munir Cochinwala, Euthimios Panagos

    Pages 142-154

11. Comparing Global Optimization and Default Settings of Stream-Based Joins

    • M. Asif Naeem, Gillian Dobbie, Gerald Weber

    Pages 155-170

12. Merging OLTP and OLAP – Back to the Future

    • Wolfgang Lehner

    Pages 171-173

13. Back Matter

    PDF

In today’s competitive and highly dynamic environment, organizations need new so- tions to enable them to solve modern business problems and to make decisions using integrated, trustworthy, and up-to-date data. Modern real-time enterprises need to act on events as they happen. They need new, easy-to-use intelligent solutions capable of analyzing heterogeneous real-time enterprise data to provide insight and actionable information at the right time. To enable real-time enterprises, we need fundamental advancements in the science and engineering that underlie intelligent information management including: the management of streaming data; the modeling, analysis and management of unstructured data; along with the integrated use of unstructured, se- structured, and structure data. We need new models and paradigms that raise the level of abstraction used in such critical technologies as ETL, data warehousing, and event and business process modeling. The series of BIRTE workshops aims to provide a forum to discuss and advance the foundational science and engineering required to enable real-time business intel- gence and the novel applications and solutions that build on these foundational te- niques. Following the success of our first workshop, BIRTE 2006, held in Seoul, Korea, in conjunction with VLDB 2006, and our second workshop, BIRTE 2008, held in Auckland, New Zealand, with VLDB 2008, our third workshop was held in Lyon, France on August 24, 2009 with VLDB 2009.

• ETL processing
• OLAP - on-line analytical processing
• OLTP - online transaction processing
• On-Line Analytical Processing
• business intelligence
• data analysis
• data warehouse
• database
• databases
• steam processing

• Hewlett-Packard, Palo Alto, USA

  Malu Castellanos, Umeshwar Dayal

• University of Toronto, Toronto, Canada

  Renée J. Miller

Policies and ethics