Summary
With this chapter, you have gained a profound knowledge of crafting batch-processing solutions within Azure’s ecosystem. You’ve mastered data integration with PolyBase, queried replicated data using Synapse Link, and orchestrated tasks through data pipelines. Now, you can seamlessly scale resources, optimize batch sizes, and ensure pipeline reliability with testing. Additionally, Python notebooks empower you with advanced data processing, upserting, and data reversion for agile data management. Finally, your expertise in exception handling, retention policies, and Delta Lakes ensures efficient handling of big data.
The next chapter will focus on how you can design and develop a stream-processing solution. You will explore the utilization of Spark structured streaming to efficiently handle data streams. Furthermore, you will gain insights into processing time-series data, managing data across partitions, and optimizing processing within a single partition. Scalability...
