Organizations realize the value data plays as a strategic asset for various business-related initiatives, such as growing revenues, improving the customer experience, operating efficiently or improving a product or service. However, accessing and managing data for these initiatives has become increasingly complex. Most of the complexity has arisen with the explosion of data volumes and data types, with organizations amassing an estimated 80% of data in unstructured and semi-structured format. As the collection of data continues to increase, 73% of the data goes unused for analytics or decision-making. In order to try and decrease this percentage and make more data usable, data engineering teams are responsible for building data pipelines to efficiently and reliably deliver data. But the process of building these complex data pipelines comes with a number of difficulties: