Customer Insights From Zoomdata and Cloudera

Understanding and preventing churn (customer loss) requires connecting to all customer touch points – transaction data, call logs, customer complains, social media engagement – to create a complete customer view in real time first. This demo then showcases how this US telco analyzes root causes of churn by discerning key behavior and customer journey, identifies customer profiles at risk accordingly, and executes plan to prevent churn proactively.



How to run an example PIG script in Cloudera’s QuickStart VM

Step-by-step process, from the very beginning, of analyzing Big Data by running a PIG script in Cloudera’s distribution of Hadoop.

If you are reading the book Big Data for Chimps and would like to follow along by running the examples, or if you just want to check out Cloudera’s distribution of Hadoop to learn what is the process for running a PIG script, or if you have a PIG script you want to try, then this tutorial is also for you.



New SQL Editor in Hue

In the Cloudera 5.8 release, Hue has an improved SQL development experience. See how SQL developers can easily explore and discover available tables through quickviews; quickly design queries with autocomplete suggestions; and get immediate assistance for debugging queries before they run for efficient troubleshooting.



Hadoop Tutorial Build a Real Time Analytic dashboard with Solr Search and Spark Streaming

Search is a great way to interactively explore your data. The Search App is continuously improving and now comes with a better support for real time!


How to use Cloudera Director on Google Cloud Platform by Gregory Grubbs

Easily and quickly provision a real CDH cluster on Google Cloud Platform. This screencast will show you how.

Table of Contents:

00:00 – Cloudera Director Overview
00:17 – What we will learn
03:52 – Installing Cloudera Director
05:50 – Instance information
07:21 – Cloudera Director Server
12:41 – The Client Config
22:20 – Running Cloudera Director Client
22:56 – Marker
30:42 – Final Notes
33:44 – Wrap up

Resources for further exploration:

Cloudera downloads:

Example Cloudera Director configuration files:… (look in configs directory)


Cloudera: Introducción a Kudu para analíticas en tiempo real

Aprovechar el valor de los datos en tiempo real, es cada vez más común entre los casos de uso de Hadoop.

Durante los últimos años el ecosistema de Hadoop ha hecho grandes progresos en sus capacidades dentro del entorno de tiempo-real, con herramientas como Impala para análisis interactivo y Apache Spark para procesos batch y en stream.

Para solventar los huecos en la capa de almacenamiento en aplicaciones de análisis en tiempo real que requieren rendimiento inmediato para el análisis sobre datos en real-time, comenzamos a observar que surgían arquitecturas híbridas complejas.

Nace Kudu como la solución a dicha complejidad. Kudu es un motor nativo de almacenamiento para Hadoop diseñado para analítica en tiempo real sobre datos en continua actualización.

Apúntate a nuestro webinar online para saber más! Te contaremos:

  • Como Nace Kudu
  • La arquitectura de Kudu y sus objetivos
  • Casos comunes de uso
  • El roadmap de Kudu y como encaja en el ecosistema de Hadoop