Are you familiar with Phyton and looking for a tool to help you plan, manage and monitor your employees’ data flows and tasks? See how we can help you by using Apache Airflow tool.
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What is Airflow?
- Apache Airflow (or simply Airflow) is one of the most popular tools written in Python. It is used to schedule multiple tasks, workflows in projects and organizations.
- The important thing to remember is that Airflow is not an ETL tool. We use code to define workflows and plan their execution.
Advantages of Apache Airflow
– thanks to ready connections, the integration becomes much simpler and faster.
Friendly interface in the web application
– You can manage all DAG workflows through the Airflow WebUl interface. Thanks to the web application we have access to the status of completed and current tasks along with an insight into their logs.
– Airflow allows you to perform tasks through a command line interface. This will allow you to restart your work from any point during the ETL process.
Simple and straightforward Airflow configuration
– Database > Schedule> Contractor> Employees
– It has a modular architecture and uses messaging to organize work for any number of employees.
– Airflow provides multiple plug-and-play connections that allow you to execute in platforms including Google Cloud Platform, Amazon Web Services, Microsoft Azure, among others.
– to transform data, manage infrastructure, and even build machine learning models, all you need is knowledge of the Phyton language.
Apache Airflow makes sense if:
- You perform complex ETL or ETL tasks on large amounts of data.
- You personally feel comfortable with Python and don’t feel like building your own ETL tool from scratch.