30.11.2016 How to Apply Big Data Analytics and Machine Learning to Real Time Processing

Update 02.12.: Folien und Videos zum Vortrag

"Big Data" is currently a big hype. Large amounts of historical data are stored in Hadoop or other platforms. Business Intelligence tools and statistical computing are used to draw new knowledge and to find patterns from this data, for example for promotions, cross-selling or fraud detection. The key challenge is how these insights and patterns can be integrated from historical data into new (future) transactions in real time to make customers happy, increase revenue or prevent fraud. "Fast Data" via stream processing is the solution to embed patterns - which were obtained from analyzing historical data - into future transactions in real-time.
This session uses real world success stories to explain the concepts behind stream processing and its relation to Hadoop, Spark, and other big data platforms. The session discusses a flexible big data architecture, different implementation patterns, best practices and pitfalls for implementing a closed loop including historical analysis, finding insights and taking them into action in real time.
A live demo discusses how a developer can leverage different technologies, frameworks and products to implement this closed loop including big data analytics, machine learning, stream processing, and human operations.  The audience will learn how to choose the right tool for the right job and how to combine them. The live demo shows how to leverage technologies and frameworks such as Apache Hadoop (Hive, HBase, Flume), Apache Spark (MLlib, SparkSQL),  Stream Processing (Apache Storm, TIBCO StreamBase), and the R language (SparkR, H2O, TERR).

Kai Wähner (@KaiWaehner) works as Technical Lead at TIBCO. Kai’s main area of expertise lies within the fields of Application Integration, Big Data, Analytics, SOA, BPM, Cloud Computing, Java EE, and Enterprise Architecture Management. He is speaker at international IT conferences such as JavaOne, ApacheCon or OOP, writes articles for professional journals, and shares his experiences with new technologies on his blog (www.kai-waehner.de/blog).
Der Vortrag ist auf Deutsch.

Der JUGF-Stammtisch findet am 30.11.2016 ab 18:30 Uhr in der Deutschen Nationalbibliothek statt.

Nach der Veranstaltung treffen wir uns wie immer noch zum Stammtisch bei Essen & Trinken in der Apfelweinwirtschaft Frank, reserviert ist ab 20:30.

Anfahrt zur Deutschen Nationalbibliothek
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