Full Resource Library
Data extraction tools significantly expedite the collection of relevant data. Learn about the tool and the benefits achieved by leveraging the right data extraction software.View Now
This video demonstrates a Data Warehouse Optimization approach that utilizes the power of Spark to perform analytics of a large dataset before loading it to the Data Warehouse.View Now
This video demonstration shows how an online bank is trying to mitigate their exposure and risk by targeting credit offers to only those customers whom are deemed low risk and most likely to accept the credit offer.View Now
This video demonstration shows how a large company with over 50,000 vending machines can use the power of IoT (Internet of Things) and machine learning to determine an individual machine’s likelihood to break down.View Now
This video shows you what to expect when you start the sandbox for the first time and how to select a Big Data Platform for evaluation.View Now
This Multiplatform Data Architectures report explains in detail what MDAs are and do, with a focus on helping data professionals and their business counterparts worldwide architect, govern, and grow their MDAs for better business outcomes via well-integrated and unified distributed data from many sources.Download Now
Since the dawn of big data, the ETL (extract, transform, and load) process has been the heart that pumps information through modern business networks. Today, cloud-based ETL is a critical tool for managing massive data sets, and one that companies will increasingly rely on in the future.View Now
ETL testing refers to tests applied throughout the ETL process to validate, verify, and ensure the accuracy of data while preventing duplicate records and data loss. Learn the 8 stages of ETL testing, 9 types of tests, common challenges, how to find the best tool, and more.View Now
With the advent of big data, data quality management is both more important and more challenging than ever. Fortunately the combination of Hadoop open source distributed processing technologies and Talend open source data management solutions bring big data quality operations within the reach of any organization.View Now
The difference between ETL and ELT lies in where data is transformed into business intelligence and how much data is retained in working data warehouses. Discover what those differences mean for business intelligence, which approach is best for your organization, and why the cloud is changing everything.View Now
In this tutorial, create Hadoop Cluster metadata by importing the configuration from the Hadoop configuration files.
This tutorial uses Talend Data Fabric Studio version 6 and a Hadoop cluster: Cloudera CDH version 5.4.
1. Create a new Hadoop cluster metadata definition
Ensure that the Integration perspective is selected.
In the Project Repository, expand Metadata, right-click Hadoop Cluster, and click Create Hadoop Cluster to open the wizard.
In the Name field of the Hadoop Cluster Connection wizard, type MyHadoopCluster_files. In the Purpose field, type Cluster connection metadata, in the Description field, type Metadata to connect to a Cloudera CDH 5.4 cluster, and click Next.