Five Ways Your Data Pipelines Are Ruining Your Data Quality

The text discusses the increasing problem of bad data in many companies due to the complexity and fragility of modern data pipelines. It highlights five main causes for this issue, including bigger and more complicated data pipeline networks, increased vulnerability of data pipelines, longer data lineages, insufficient traditional data quality testing, and the impact of data democracy on data pipelines. The text suggests that a modern data governance and data quality solution is needed to address these issues, with features such as automated data discovery, constant data reliability checks, machine learning-powered predictive analysis, and a 360-degree view of the entire data infrastructure.