Running Big Data Jobs using Prefect

Prefect

Prefect is an open-source workflow management system that allows you to build, schedule, and monitor data workflows. It enables you to transform any Python function into a unit of work that can be observed and orchestrated. Prefect can be used for various use cases such as ETL pipelines, machine learning workflows, data warehousing, and more. It has a dynamic engine and ephemeral API that makes it easy to run workflows interactively during the building phase. Prefect also offers the ability to cache and persist inputs and outputs for large files and expensive operations, improving development time when debugging.

Big Data

Big data refers to data that is so large, fast or complex that it's difficult or impossible to process using traditional methods. It can be a combination of structured, semi-structured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling and other advanced analytics applications. Big data technology deals with data storage that has the capability to fetch, store, and manage big data. It allows users to store the data so that it is convenient to access. Big data analytics helps companies leverage their data to identify opportunities for improvement and optimization. Across different business segments, increasing efficiency leads to overall more intelligent operations, higher profits, and satisfied customers.
Open source orchestrators like Prefect are one of the primary means by which companies leverage big data in production. Prefect offers a mechanism to schedule and monitor these jobs as part of more complex workflow graphs. Kaspian has a native operator for Prefect; this operator makes it easy to either swap to or get started with running Big Data jobs that utilize Kaspian's flexible compute layer.
Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.

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