What is a data pipeline? A data pipeline is a sequence of data processing actions that automatically moves data from one or more sources to a target destination.
Effectively managing your data is essential to implement data-driven marketing strategies that drive revenue for your business. But organizing and managing your data from multiple sources can be tricky. That’s where data pipelines can help.
So, what is a data pipeline, and how does it work? If these questions are currently on your mind, we’ve got the perfect guide for you.
Check out some of the topics we’ll cover below, and then keep reading to learn more!
- What is a data pipeline?
- How does a data pipeline work?
- The data pipeline process
- Data pipeline vs. ETL pipeline: What’s the difference?
- Why use a data pipeline?
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What is a data pipeline?
A data pipeline is a sequence of actions that moves data from a source to another destination. Data pipelines can help you transfer data from one source, like your website, to a destination, like a data warehouse, for analysis and interpretation.
How does a data pipeline work?
Your company likely deals with a large amount of data. It’s essential to have a single view of all of your data to analyze all of your metrics and information to gain actionable insights.
But if your data comes from multiple platforms, tools, and devices, you’ll need to organize and combine it to analyze it effectively. You might be thinking you could copy and paste your data from one source to another to combine it. However, this method can lead to data corruption or bottlenecks, making your collected data useless.
That’s where data pipelines come in. To understand how a data pipeline works, think of it as a water pipe that carries water from one location to another.
A data pipeline works the same way. It takes data from one or multiple sources, like a customer relationship platform (CRM) or analytics tool, and safely transfers it to another destination, like a data warehouse, so that you can organize and analyze your data all in the same place.
The data pipeline process
Now that you know what a data pipeline is and how it works, let’s take a look at the data pipeline process below:
The first stage in a data pipeline is to take data from one or more sources. A source can be a:
- Relational database
- CRM platform
- Enterprise resource planning (ERP) platform
- Social media management tool
- And more
With most pipelines, you can pull data from specific sources in real-time at scheduled intervals to ensure you collect and store all of your data regularly.
Once your data pipeline has ingested data from a source, it will process it. In some cases, data pipelines can manipulate and change your data before transferring it to its final destination.
The processing stage can include:
- And more
Data processing can organize your data and make it easier to analyze once it’s transferred to the next destination.
The last stage in a data pipeline is to transfer the data to its target destination. In most cases, you’ll use your data pipeline to transfer your data to a large-scale storage platform so you can store your data in one place.
Your destination can include a:
- Data warehouse: A data warehouse enables you to store, manage, and organize data. It usually has dashboards, analytics tools, and reporting features to help you analyze and interpret your data.
- Data lake: A data lake is a system that allows you to store raw, unprocessed data at any scale
- Datamart: A data mart is a smaller, data storage option that usually focuses on one subset of data, like sales or leads.
Once the data pipeline transfers your data, you can then analyze it to identify actionable insights. You can then use these insights to improve your marketing strategies to drive better results for your business.
Data pipeline vs. ETL pipeline: What’s the difference?
If you’ve heard of an ETL pipeline, you might think it’s the same as a data pipeline, but the two terms are different. Let’s go over some of the main differences between a data pipeline vs. ETL pipeline below:
ETL pipeline stands for “extract, transform, and load” and is a specific type of data pipeline. In other words, you can think of ETL pipelines as a subcategory of data pipelines.
With an ETL pipeline, you can extract data from a source, transform it and load it to another destination, like a data warehouse.
The biggest difference between an ETL pipeline and a data pipeline is that ETL pipelines transform your data more than a data pipeline can. For example, you can use ETL pipelines to transform your data to align with your business goals, like combining specific metrics to make your data easier to analyze.
In addition, ETL pipelines typically transfer your data in set schedules when network traffic slows down instead of in real-time. That means your data will transfer at regular intervals instead of continuously.
Like an ETL pipeline, a data pipeline enables you to take data from one source and transfer it to another.
While some data pipelines can transform and process your data, this isn’t always a characteristic of all data pipelines, while all ETL pipelines transform your data.
Data pipelines are always up and running, which means they can transfer your data in real-time. As a result, you can use a data pipeline to update your data continuously.
Why use a data pipeline?
So, why use a data pipeline? Today, more companies harness the power of data to create effective marketing strategies that help them stand out from their competitors and drive more revenue. Odds are, if you aren’t using data to inform your campaigns, your competitors most likely are.
Data pipelines help you organize and manage essential data and information about your marketing strategies, customers, leads, and more.
Without a data pipeline, your data won’t be stored or organized in one central place. If you don’t keep your data in the same place, it’s challenging and time-consuming to analyze your data and identify trends and actionable insights.
When you use a data pipeline, you can seamlessly transfer your data between multiple sources and combine it in a central location so that you can analyze and interpret it later. You can then use your insights to inform your marketing strategies.
For example, you might notice that most of your leads come from your pay-per-click (PPC) ads. As a result, you can use that insight to optimize your PPC campaign to drive more web traffic and leads for your business.
What is a data pipeline? Let’s recap
That was a lot of information we went over in this data pipeline guide. Let’s recap everything you just learned:
- A data pipeline is a set of operations designed to automatically move data from one or more sources to a target destination
- You can use a data pipeline to transfer data from one source, like a CRM platform, to another destination, like a data warehouse.
- The three data pipeline stages are: Source, processing, and destination
- The biggest difference between a data pipeline vs. ETL pipeline is that ETL pipelines transform your data in a way that makes it easier to analyze and only transfers your data to another destination during scheduled intervals
- Data pipelines can help you track, organize, and manage your data to help you identify actionable insights to inform your marketing strategies
Do you want to learn more about data-driven marketing? Then check out our top five tips for using data to drive better marketing results below!
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