To understand the complexity of modern data environments, consider their many elements. Databases such as Oracle or MongoDB, applications such as Salesforce or Slack, analytics platforms such as Snowflake or BigQuery, and BI/data science tools such as Qlik or Tensorflow all must share data with one another. They depend on pipelines to deliver the right data to the right target in the right format—on time. Compounding the complexity, data engineers and other stakeholders must contend with multiplying users, use cases, projects, devices, tools, applications, and platforms.