In the context of digital transformation, many companies, especially smaller firms or startups with limited resources, face challenges in building and maintaining data pipelines. Constructing these pipelines is labor-intensive, requiring significant time and effort from solo data analysts or engineers, who must handle tasks like obtaining data access, designing schemas, and coding connectors. This approach often leads to scalability issues and increased maintenance demands as new data sources are added. Companies like the fintech startup Billie have found that using off-the-shelf automated solutions provides a more efficient and scalable alternative, enabling a single engineer to manage tasks once requiring a larger team. Similarly, Raider Express, a trucking company, leverages a fully managed solution such as Fivetran to handle real-time data syncing with minimal upkeep, allowing them to focus on actionable insights rather than pipeline maintenance. This highlights the importance for resource-strapped companies to prioritize automated solutions, allowing their data professionals to concentrate on analyzing data and generating valuable insights for growth.