Oracle Data Integrator Enterprise Edition Advanced Big Data Option Part 1- Overview and 12.1.3.0.1 install

Monday, April 13th, 2015 by

Oracle recently announced Oracle Data Integrator Enterprise Edition Advanced Big Data Options as part of the new 12.1.3.0.1 release of ODI. It includes various great new functionalities to work on an Hadoop ecosystem. Let’s have a look at the new features and how to install it on Big Data Lite 4.1 Virtual Machine. Note that some of these new […]

New Oracle Big Data Quick-Start Packages from Rittman Mead

Wednesday, March 25th, 2015 by

Many organisations using Oracle’s business intelligence and data warehousing tools are now looking to extend their capabilities using “big data” technologies. Customers running their data warehouses on Oracle Databases are now looking to use Hadoop to extend their storage capacity whilst offloading initial data loading and ETL to this complementary platform; other customers are using […]

Introducing Oracle Big Data Discovery Part 2: Data Transformation, Wrangling and Exploration

Wednesday, February 25th, 2015 by

In yesterday’s post I looked at Oracle Big Data Discovery and how it brought the search and analytic capabilities of Endeca to Hadoop. We looked at how the Oracle Endeca Information Discovery Studio application works with a version of the Endeca Server engine to analyse and visualise sample sets of data from the Hadoop cluster, […]

Connecting OBIEE11g on Windows to a Kerberos-Secured CDH5 Hadoop Cluster using Cloudera HiveServer2 ODBC Drivers

Sunday, December 28th, 2014 by

In a few previous posts and magazine articles I’ve covered connecting OBIEE11g to a Hadoop cluster, using OBIEE 11.1.1.7 and Cloudera CDH4 and CDH5 as the examples. Things get a bit complicated in that the DataDirect Apache Hive ODBC drivers that Oracle ship are only for HiveServer1 and not the HiveServer2 version that CDH4 and […]

Going Beyond MapReduce for Hadoop ETL Pt.2 : Introducing Apache YARN and Apache Tez

Monday, December 8th, 2014 by

In the first post in this three part series on going beyond MapReduce for Hadoop ETL, I looked at how a typical Apache Pig script gets compiled into a series of MapReduce jobs, and those MapReduce jobs pass data between themselves by writing intermediate resultsets to disk (HDFS, the Hadoop cluster file system). As a […]

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