Lesson 19 – Quick overview on Data Pipeline connectors

In the business world, making informed decisions is all about leveraging data. However, handling data efficiently is not an easy task. That’s where data pipelines come into play, simplifying the process of moving and transforming data to make it more manageable and useful.

Data pipeline connectors

Data pipeline connectors are tools that enable the seamless flow of data between different sources and destinations in a data pipeline. They extract data from various origins, transform it according to specific rules, and then load it into designated destinations such as data warehouses or lakes. These connectors ensure efficient, real-time, and reliable data movement, supporting organizations in making informed decisions and driving insights.

Data pipeline connectors used for various purposes such as

Extracting data from various sources, such as databases, files, etc.
Transforming data according to pre-defined rules such as aggregation, filtering etc.
Loading transformed data into various destinations such as cloud storage, workspace etc.
Monitoring the quality, performance and security of data.
Assists in automating and streamlining your data integration processes, reducing errors and latency.

Key features of data pipeline connectors

Real-time Processing – Facilitates continuous movement and transformation for timely insights.
Fault-tolerant Design – Recovers from failures and errors to ensure data quality and consistency.
Scalable Architecture – Adapts to varying data volumes and velocities, accommodating changes in sources and formats.
Exactly-Once Processing (E1P) – Guarantees that each data record undergoes processing only once, preventing duplicates.
User-Friendly Management – Easily configured and monitored by users without the need for extensive coding or maintenance.

Data pipeline connectors in Microsoft Fabric

The tables below present a list of current data pipeline connectors categorized for Microsoft Data Factory in Microsoft Fabric.

Azure