What Is a Data Pipeline in Hadoop? Where and How to Start

what is a data pipeline in hadoop

Did you know that Facebook stores over 1000 terabytes of data generated by users every day? That’s a huge amount of data, and I’m only talking about one application! And hundreds of quintillion bytes of data are generated every day in total.

With so much data being generated, it becomes difficult to process data to make it efficiently available to the end user. And that’s why the data pipeline is used.

So, what is a data pipeline? Because we are talking about a huge amount of data, I will be talking about the data pipeline with respect to Hadoop.

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How to Build a Data Management Platform: A Detailed Guide

how to build a data management platform

Does your business need to gain better data insights? Would you like to collect, organize, and activate data from any source, be it online, offline, mobile, and more? Then you need a data management platform, or DMP.

Let’s start with a brief introduction to DMPs. Data management platforms allow you to organize, collect, and activate audience data from any source. Through this, a DMP will add value to your business by providing insights about your customers.

Today, you can buy a DMP from a number of vendors. However, the cost usually ranges from $80K to over $1M for large implementations.

But don’t fret—you have another option. You can build one yourself.

In this post, I’m going to explain how a data management platform works, features of a DMP, and the architecture for building a DMP.

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What Is Data Preparation? Intro, How-to, and Best Practices

Data preparation is an important aspect of data management. It helps your organization by combining data from multiple raw sources into one valuable, high-quality dataset. Data preparation is an essential step toward improving processes and making informed, data-driven decisions.

This article will help you understand what data preparation is and when to use it. Also, this article will explain four simple data preparation steps to get you started.

Let’s first learn the basics of data preparation.

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