This IBM® Redpaper publication focuses on data orchestration in enterprise data pipelines. It provides details about data orchestration and how to address typical challenges that customers face when dealing with large and ever-growing amounts of data for data analytics. While the amount of data increases steadily, artificial intelligence (AI) workloads must speed up to deliver insights and business value in a timely manner.

This paper provides a solution that addresses these needs: Data Accelerator for AI and Analytics (DAAA). A proof of concept (PoC) is described in detail.

This paper focuses on the functions that are provided by the Data Accelerator for AI and Analytics solution, which simplifies the daily work of data scientists and system administrators. This solution helps increase the efficiency of storage systems and data processing to obtain results faster while eliminating unnecessary data copies and associated data management.

Chapter 1. Data orchestration in enterprise data pipelines

Chapter 2. Data Accelerator for AI and Analytics supporting data orchestration

Chapter 3. Data Accelerator for AI and Analytics use cases

Chapter 4. Planning for Data Accelerator for AI and Analytics

Chapter 5. Deployment considerations for Data Accelerator for AI and Analytics

Appendix A. Code samples