Data Engineering

  Data engineering is a field that involves the design, development, and management of systems that collect, store, process, and analyze data. It is an essential component of data science and plays a crucial role in enabling organizations to make data-driven decisions. Data engineering can be divided into three main areas: data ingestion, data processing, and data storage. Data Ingestion: This involves collecting data from various sources, such as databases, APIs, sensors, and other data streams. The collected data must be processed and transformed into a format that is suitable for analysis. Data engineers use tools such as Apache Kafka, Apache NiFi, and AWS Kinesis to collect and manage data streams. Data Processing: Once the data is collected, it must be processed and transformed into a format that is suitable for analysis. This involves cleaning, filtering, and aggregating the data to remove any inconsistencies or errors. Data engineers use tools such as Apache Spark, Apa...