Engineering a big data ingestion pipeline is complicated – if you don’t have the right tools.
All data, be it big, little, dark, structured, or unstructured, must be ingested, cleansed, and transformed before insights can be gleaned, a base tenet of the analytics process model.
You don’t have to look far to see that businesses are leveraging big data in creative ways. They use it to run their day-to-day operations or to convince us to buy more stuff or even to deliver better healthcare. These data success stories are made possible because of new and emerging technologies like Hadoop, and Talend’s Big Data Platform.
Hadoop, and its ecosystem of tools and technologies, enables distributed processing of data at Exabyte scale. Hortonworks, a leader in this technology space, is simplifying the process of big data batch and real-time analytics.
Talend’s Big Data Platform seamlessly integrates with Hortonworks, as well as with the other major Hadoop distributions. Talend puts the power of big data analytics into the hands of users who traditionally depend on specialists like data engineers. With an intuitive approach to data ingestion pipeline design, Talend helps organizations minimize the time to value of their most important asset - their data.
In the following knowledge base article, I demonstrate the ease of creating a big data pipeline with Talend. Everything you need to get started is readily available, including example data and the software used in the demonstration.
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As always, I am interested in hearing your thoughts on this topic and encourage your feedback.