One MSc thesis to be presented on October 28, 2016.
There will be one MSc thesis presentation in E:2116 at 13.15 on October 28, 2016.
Note to potential opponents: Register as opponent to the presentation by sending an email to the examiner (firstname.lastname@example.org). Note that the number of opponents may be limited (often to two). Registrations are individual, just as the oppositions are! More instructions are found on this page.
Place: E:2116 Time: 13:15
|TITLE||Big Data Business Rules|
|SUPERVISORS||Pierre Nugues (LTH), Peter Exner (LTH), Matteo Casalino (Amadeus)|
Business Rules Engines are systems created to deliver relevant business information to applications and business processes. Given the critical position of a rule engine, efficient rule search is essential. However, since the advent of Big Data, efficient rule search has become increasingly difficult -- more data leads to more rules.
In this thesis we prototype a rule engine in the Big Data framework Apache Spark, opening up the world of business rules for Big Data applications.
Furthermore, a performance study is conducted, benchmarking the performance and scalability of the prototype against the Amadeus Business Rules engine, ABR.