Data Analytics: Building Pipelines with Azure Data Factory

Azure Data Factory- It is a cloud-based ETL and data integration service that allows you to create data-driven workflows for orchestrating data movement and transforming data at scale, we can say an advanced version of a traditional cloud ETL tool similar to SSIS. Data Factory provides a data integration and transformation layer that works across your digital transformation initiatives

It has so many In-built connectors that will be helpful for fetching data from Big Data sources. ADF can handle -Structured & Unstructured data at an unlimited scale. This change has shifted the paradigm for loading and transforming data from ETL to extract, load, and transform (ELT).

Two common types of data integration patterns can be supported by Azure Data Factory.

1. Modern Data Warehouse workloads: A Modern Data Warehouse provides descriptive analytics and decision support services across the whole enterprise using structured, unstructured, or streaming data sources. Azure Data Factory supports- data flows into the warehouse from multiple transactional systems, relational databases, and other data sources periodically

2. Advanced Analytical Workloads: We perform advanced analytics in the form of predictive or preemptive analytics using a range of Azure data platform services. Azure Data Factory provides the integration from source systems into a Data Lake store and can initiate compute resources such as Azure Databricks, or HDInsight to use the data to perform advanced analytical work.

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