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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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2 Exclusive Ways to Start Kafka Services

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The Kafka services start or stop you can do in two ways. Those are  Systemd  and  Systemctl  (sudo user). Below, you will find the commands for these two methods. How to start/stop Kafka service Here are exclusive ways. With these, you can start or stop Kafka services .   1. Systemd service The concept of unit files people who worked on Linux servers have familiarity with it. Also, they know creating the unit file to use by systemd. To summarize,  it initializes and maintains components throughout the system . This means that you can define ZooKeeper and Kafka as unit files, which then will be used by systems. Commands The first command starts the service, and the second command stops the service. ... [Service] ... ExecStart=/opt/kafkainaction/bin/zookeeper-server-start.sh ExecStop= /opt/kafkainaction/bin/zookeeper-server-stop.sh 2. Systemctl by Sudo (root) user The root user can start or stop the Kafka services. This is more like front-end processing...
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