Data Pipeline Orchestration

Why the road to AI starts with data pipeline orchestration

Data will decide who wins the AI race. However, most data engineering teams are drowning in technical and organizational complexity when working to implement processes such as ETL workflows or data ingestion pipelines. To succeed, you need to repeatedly combine data from diverse and disparate data sources and make it available for downstream applications, data science projects and AI solutions.

Data pipeline orchestration, a pillar of DataOps, helps standardize and simplify these workflows, speeding the path for AI and ML while following best practices such as ensuring data quality and data observability. Learn what orchestration is, why it’s important and how to choose the right orchestrator in this new report by Eckerson Group.

You’ll discover:

• An overview of challenges, adoption drivers and market evolution of data orchestration
• Guiding principles for selecting an orchestration tool
• Why Databricks Workflows — the unified orchestration tool for the Data Intelligence Platform — may be right for you