The phrase 'data engineering tools' refers to a broad category of technologies that comprise the contemporary data stack. Modern data stacks require specialized technologies to speed up data integration engineering. These connectors are scalable to accommodate your expanding data needs, end-user-centric, and independent of the cloud. Data engineering tools typically assist with the following: Building a pipeline for data.Facilitating efficient ETL/ELT processes.Creating reports using data visualization and business intelligence. Let's briefly go over them with a few examples and the Importance of data engineering. Data Integration: Fully managed ETL tools are necessary to offer real-time or almost real-time data for

ETL refers to the three separate but interlaced processes involved in exchanging data between systems. Extract, Transform and Load. Extract: This function connects to a specified data source and accesses the data required for the process ready to be loaded into a different application / database. Transform: Transform stage will typically carry out data quality […]

ETL - Extract, Transform, Load