Learning case studies from the logistics and supply chain industry
Data analytics and machine learning play a crucial role in the functioning of the logistics and supply chain industry. Data can help reduce inefficiencies in the supply chain processes and optimize deliveries at the same time. Machine learning and predictive analytics help in better planning, procurement, and consumer fulfillment.
Case study 9 – accelerating intelligent insights with tailored big data analytics
An organization wanted to create an end-to-end data warehousing platform on Azure. Their original process involved manually collecting data from siloed sources and creating necessary reports from it. There was a need to integrate all the data sources and implement a single source of truth, which would be on the Azure cloud. The proposed solution architecture was as follows:
- Full load and incremental data pipelines were developed using Azure Data Factory to ingest data into Azure Synapse...
