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Leveraging your Db2 Skills with Big Data

Leveraging your Db2 Skills with Big Data Jim Wankowski, IBM The Challenge The idea of the traditional data center being centered on relational database technology is quickly evolving. Many new data sources exist today that did not exist as little as 5 years ago. Devices such...

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Apache Spark and IBM Machine Learning on z/OS

Article by George Wang, IBM and Kewei Wei, IBM Introduction Analytics is increasingly an integral part of day-to-day operations at today's leading businesses, and transformation is also occurring through huge growth in mobile and digital channels. Enterprise organizations are...

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Big Data and SQL

My introduction to DB2 and SQL occurred over 30 years ago. It changed my life. Before that, I’d been working with IMS databases. Every ad hoc process/report required us to write a program. Every program required a predetermined database access module before we could run that program....

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The End of DB2?

ACID transactions in Hadoop vs. ACID transactions in DB2 Ludovic Janssens Introduction ACID transactions have been a standard for databases since the seventies. The standard requires transactions to have the following properties: Atomicity – the database may only be affected when...

Blog Entry
Using Apache Spark with DB2 for z/OS and z Systems Data

Apache Spark has become a very hot topic in the world of Big Data Analytics. It is seen as an alternative to Map/Reduce with superior performance due to more in-memory processing, and as a means to perform analytics that combine a wide set of data sources. IDUG had a one-day track of Spark...

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DB2 z/OS as a Modern Enterprise Data Warehouse

DB2 z/OS as a Modern Enterprise Data Warehouse The sturgeon may be a prehistoric animal, but there can be great caviar inside by Ludovic Janssens, Infocura Introduction: what makes an EDW future proof? The subtitle of this article refers to Alan Reddings blog [1] who calls the...

Library Entry
E07 - IBM Data Retrieval Technologies: RDBMS, BLU, IBM Netezza, and Hadoop

IBM offers four distinct data retrieval technologies: the traditional RDBMS, which primarily relies on indexes to speed access; the new BLU Acceleration columnar compression database; IBM PureData System for Analytics (IBM Netezza), which deploys racks of Field Programmable Gate Array (FPGA)...

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Library Entry
David Barne's IDUG EMEA Keynote Presentation; What Matters Next in Big Data

David Barnes is indeed a very entertaining and inspiring speaker. David’s 90/90 rules says it all, 90% of the world’s data may be unstructured, but the 90% of the data that is important is already well taken care of, by US…, today’s data management practitioners and tomorrow’s data scientists....