Data is at the heart of every organization and Data Pipeplines are the new transportation means to transfer the data (information) from one end to the other.

The procedures required to address issues of data extraction and transformation are eliminated by data pipelines, It would transform the procedures into an efficient, automated workflow. You must first identify the exact issues that will affect your design before you can actually start developing a data pipeline. Think about it:

What is the purpose of the pipeline? What do you hope to achieve with the pipeline and why do you need it? Will the data transfer be one-time only or repeated?
What sort of information is involved? How much data do you anticipate using? Is the data structured or unstructured, flowing or stored?
What purpose will the data serve? Will the data be utilised for business intelligence, reporting, analytics, data science, automation, or machine learning?
You have a choice between three generally acknowledged methods for building a data processing pipeline architecture once you have a deeper understanding of the design variables.



By Pankaj

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