![]() ![]() Billions of data events from sources as varied as SaaS apps, Databases, File Storage and Streaming sources can be replicated in near real-time with Hevo’s fault-tolerant architecture. Broken pipelines, data quality issues, bugs and errors, and lack of control and visibility over the data flow make data integration a nightmare.ġ000+ data teams rely on Hevo’s Data Pipeline Platform to integrate data from over 150+ sources in a matter of minutes. Yet, they struggle to consolidate the scattered data in their warehouse to build a single source of truth. Here’s why you need Airflow Github Integration:Īs the ability of businesses to collect data explodes, data teams have a crucial role to play in fueling data-driven decisions. In this blog, we’ll provide an overview of these platforms and steps for Airflow Github Integration. When hearing Python, we all know the greatest source for all the Python codes, Github, Github is a powerful tool with many advantages, but it requires careful tailoring to fit perfectly into any given process chain. ![]() While other “configuration as code” workflow platforms exist that use markup languages such as XML, Python allows developers to import libraries and classes to help them create their workflows. The airflow is designed using the “configuration as code” principle. These are workflows for the data teams in charge of ETL pipelines, and a code-based system may simply play to the strengths of your tech-savvy team members.Īirflow is written in Python, and workflows are built using Python scripts. Getting Started with Airflow Github Integration. ![]()
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