Data is widely considered the lifeblood of an organization; however, it is worthless—and useless—in its raw form. Help is needed to turn this data into life-giving information. Part of this help is to move this data from its source to its destination via data pipelines. However, managing the end-to-end data pipeline lifecycle is not easy: some are challenging to scale on demand, and others can result in delays in detecting and addressing issues or be difficult to control. These and the other problems may be solved in the declarative programming paradigm, and in this article, we will see it on Terraform. 

Where Does This Data Come From? 

The data in these extensive datasets come from multiple disparate sources and are typically loaded into datasets in data storage like ClickHouse via data pipelines. These pipelines play a critical role in this process by efficiently moving, transforming, and processing the data. 

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