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In addition to the rapidly-increasing amount of external data companies collect, volumes of internal data are constantly generated from customers, partners, product engineering teams, and operational teams in organizations every day. Most generated data is stored in inconsistent formats across data silos, warehouses, data lakes, and lakehouses, and finding relevant data is almost as hard as accessing it.
A traditional data pipeline moves data from the source to the destination, but multiple pipelines can originate from the same source. Data pipelines were originally designed to connect data from multiple sources and collect it into a single storage system, and another level of pipelines are built to move collected data into an algorithmic solutions platform. With the constant need for data pipelines and connections, keeping up with existing pipelines while constantly building new ones is time-consuming and expensive, both financially and in terms of resources.
Data pipelines are still an integral part of many organizations, but the increased number of data stores and changing data demands across decision makers are making the data pipeline seem like a legacy technology. Data flows have emerged as a modern take on the traditional pipeline, providing expanded functionality and usability as well as the flexibility to scale to meet modern data needs.
Why Traditional Data Pipelines are Hard to Work With
Data pipelines are built on a linear structure to follow the flow of data, while modern data requirements are ascertained based on customer inputs, value comparisons, third-party access, and data development.
How Data Flows Address Modern Data Needs
Conclusion
While the terms ‘data pipeline’ and ‘data flow’ are often used interchangeably, they describe different versions of the same process. Drawing the distinction between the two and upgrading from data pipelines to data flows is an integral building block of a modern data solution, and using the correct term can mean the difference between manually maintaining a pipeline and automating a robust flow. Which option are you using?
Next Steps
If you’re looking for more information about how Nexla is automating data engineering, get a demo or book your free unified data solution strategy session today. For more on data and data solutions, check out the other articles on Nexla’s blog.
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