Visualizing Big Data

Hadoop, Tableau

This post explores using Tableau Server to visualize data in a Hadoop cluster.

More and more businesses are finding value or savings in replumbing their databases to be deployed on commodity hardware running open-source software like Cloudera Distribution of Hadoop. With tools like Impala, realtime queries of massive datasets become possible. To get the most insight, compelling interactive data exploration and visualization is necessary. We wanted to explore how Tableau works in this regard, and found Tableau Server visualizing data from CDH using Impala proved facile. This combination provides data exploration at the speed of thought with beautiful intuitive visualizations, resulting in a quick front-end for big data.

Big Data Discovery – Custom Java Transformations Part 2

BDD, BigData, Hadoop, Tips And Tricks

In a previous post, we walked through how to implement a custom Java transformation in Oracle Big Data Discovery.  While that post was more technical in nature, this follow up post will highlight a detailed use case for the transformations and illustrate how they can be used to augment an existing dataset.

Big Data Discovery - Custom Java Transformations Part 1

BDD, BigData, Hadoop, Tips And Tricks

In our first post introducing Oracle Big Data Discovery, we highlighted the data transform capabilities of BDD.  The transform editor provides a variety of built in functions for transforming datasets.  While these built in functions are straightforward to use and don't require any additional configuration, they are also limited to a predefined set of transformations.  Fortunately, for those looking for additional functionality during transform, it is possible to introduce custom transformations that can leverage external Java libraries by implementing a custom Groovy script.  The rest of this post will walk through the implementation of a basic example, and a subsequent post will go in depth with a few real world use cases.

Bringing Data Discovery To Hadoop - Part 2

BDD, BigData, Hadoop, Spark

The most exciting thing about Oracle Big Data Discovery is its integration with all the latest tools in the Hadoop ecosystem. This includes Spark, which is rapidly supplanting MapReduce as the processing paradigm of choice on distributed architectures. BDD also makes clever use of the tried and tested Hive as a metadata layer, meaning it has a stable foundation on which to build its complex data processing operations.

About Edgewater Ranzal

Edgewater Ranzal is an integrated Business Analytics solution provider deeply rooted in Enterprise Performance Management (EPM). Coupled with our Business Intelligence (BI) and Big Data (BD) expertise, we provide holistic solutions that help organizations define, measure, and innovate their business, provide a clear vision, and drive business value.

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