7 challenges that data pipelines must solve

The text discusses the challenges faced by data pipelines due to the current data landscape, including issues with connecting to stored data, batch importing of stock data, limitations in handling variable-length events, and more. It also highlights previous attempts and lessons learned from these scenarios. Furthermore, it presents seven key challenges that modern data pipelines need to overcome: getting data where needed, hosting and storing data, flexibility in data, scaling with data, moving data around, mashing up and transforming data, and visualizing everything. The text concludes by emphasizing the importance of choosing the right tools and services for building effective data pipelines.

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