"Big Data Applications in Finance"
Innovation Enterprise: Big Data in Finance Summit, Boston, November 2014.
Financial service organizations generate huge volume of data and have relied on data analytics for quite some time. But the intense search for competitive advantage in finance points to Fast Data rather than Big Data as the secret weapon in many financial domains. Innovation Enterprise.
"Big Data, Simple and Fast: Addressing the Shortcomings of Hadoop"
Webinar, October 2014
This talk identifies several shortcomings of Apache Hadoop and presents an alternative approach for building agile and flexible Big Data software stacks quickly, based on the next generation computing paradigm - in-memory data/compute grids. Download slides. Watch on YouTube. Download code samples (.zip)
"The Future of Real-time Big Data: Distributed In-Memory Data Grids"
New England Java User Group, Boston, March 2014.
High-velocity data stream computing means real-time tracking, aggregation and analysis of rapidly changing data streams originating from different sources delivered in disparate formats. This presentation describes several key business use cases and the requirements they introduce. It then provides a vendor-neutral, detailed comparative analysis of several enabling technologies and platforms/software stacks built on top of them, and introduces and discusses the concept of Unified Big Data Processing. Download slides.
"Avoiding a SOA Fiasco. An Ounce of Prevention is Worth a Pound of Cure."
SOA World, New York City, June 2008.
This presentation covers a list of the most important risk factors in Service Oriented Applications (SOA) projects and ways to mitigate them before it is too late. The presentation will be of interest to anyone planning an SOA initative, primarily CIOs, Technical Managers, Project Directors and Technical Architects.
Persist Data with Java Data Objects, Pt. 1.
Jacek Kruszelnicki, JavaWorld, March 1, 2002
The Java Data Objects (JDO) standard provides a unified, simple and transparent persistence interface between Java application objects and data stores. It can significantly affect how we deal with persistent data. In this article, Jacek Kruszelnicki discusses the issues encountered with persistence, presents traits for an ideal persistence layer, and reviews available JDO solutions. Java World Article.
Persist Data with Java Data Objects, Pt. 2.
Jacek Kruszelnicki, JavaWorld, April 12, 2002
The Java Data Objects (JDO) standard provides a unified, simple, and transparent persistence interface between Java application objects and data stores, and can significantly affect the way we deal with persistent data. This article presents two major JDO specifications: the Sun Microsystems JDO and the open source Castor JDO. Jacek Kruszelnicki discusses their relative pros and cons, and their similarities and differences. Java World Article.