Big Data Analytics Using Azure Synapse Analytics

Traditional analytics done on structured and relational data helps with analyzing transactional data. This worked well until the dotcom revolution, which saw an influx of large volumes of semi-structured data such as shopping carts, customer profiles, and ad clicks. A new type of technology was needed to process big data considering its volume. Due to this, data processing methods such as MapReduce became popular (to learn more about MapReduce, please refer to https://learn.microsoft.com/en-us/azure/hdinsight/hadoop/apache-hadoop-introduction). This led to technologies such as Hadoop and – later – Apache Spark becoming the new big data processing engines.

In this chapter, we will look at Azure services that can help you build a data mesh landing zone template for big data processing. We will cover one possible architecture for handling and analyzing big data by covering these topics:

• Requirements
• Architecture...