What Is a Data Pipeline?
A data pipeline is a series of data processing steps. If the data is not currently loaded into the data platform, then it is ingested at the beginning of the pipeline. Then there are a series of steps in which each step delivers an output that is the input to the next step. This continues until the pipeline is complete. In some cases, independent steps may be run in parallel.
Data pipelines consist of three key elements: a source, a processing step or steps, and a destination. In some data pipelines, the destination may be called a sink. Data pipelines enable the flow of data from an application to a data warehouse, from a data lake to an analytics database, or into a payment processing system, for example. Data pipelines also may have the same source and sink, such that the pipeline is purely about modifying the data set. Any time data is processed between point A and point B (or points B, C, and D), there is a data pipeline between those points.
Benefits of Using Data Pipelines
Data pipelines done right have incredible advantages for companies and organizations, and the work they do.
Real-time Analytics and Applications
Real-time or near real-time functionality in consumer and business applications puts the pressure on data pipelines to deliver the right data, to the right place, right now. Streaming data pipelines deliver continuous data to real-time analytics and applications.
Self-service Data
Data pipelines that can be created ad hoc by data scientists and business analysts. That means when people have brilliant ideas, they can test them, fail fast, and innovate faster.
Accelerate Cloud Migration and Adoption
Data pipelines help you expand your cloud presence and migrate data to cloud platforms (yes, that’s with an s). Cloud computing helps you feed many new use cases at processing speeds, cost-effectiveness, and bursting capacity unheard of in traditional on-premises data centers. Plus your team can take advantage of rapid innovation happening on those cloud platforms such as natural language processing, sentiment analysis, image processing, and more.
How ODF Can Help
Instant Data Integration
Updates and historical data from all corners of the business available in one place for analytics and insight independently of each other
Real-Time Data and Analytics
Access real-time data as it's generated without sacrificing data quality, consistency, or security. Get powerful real-time insights, and analytics in milliseconds, unlocking new business value and new customer experiences
Cost-Efficiency
Free up engineers and IT from endless monitoring, configurations, and maintenance. Save on development costs and improve organizational efficiency
Infinite Scale
Scale your data infrastructure to meet and manage current, future and peak data volumes
Multi-Cloud Flexibility
Connect to data regardless where it resides - on-prem data silos, cloud services, or serverless infrastructure
Broad Connectivity
Scalable, fault-tolerant data import and export to over a hundred data systems