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The process of merging and summarizing data from various sources in order to generate insightful conclusions is known as dataaggregation. The purpose of dataaggregation is to make it easier to analyze and interpret large amounts of data. This can be done manually or with a datacleansing tool.
The transformation is governed by predefined rules that dictate how the data should be altered to fit the requirements of the target data store. This process can encompass a wide range of activities, each aiming to enhance the data’s usability and relevance. Read More: Zero ETL: What’s Behind the Hype?
It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a datalake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.
This project is an opportunity for data enthusiasts to engage in the information produced and used by the New York City government. to accumulate data over a given period for better analysis. In this project, you will explore the usage of Databricks Spark on Azure with Spark SQL and build this data pipeline.
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