What Is A Data Pipeline?
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Written by Openbridge Support
Updated over a week ago

Do you need access to Amazon Seller Central data? Marketing data from Instagram, Facebook, Amazon Advertising, or Google Ads? Do you want to unify this data in a private, trusted, and easy-to-use data lake or cloud warehouse? Data pipelines are exactly what you need to accomplish this goal.

Data Source To Data Destination

A data pipeline reflects a connector from a specific data source, say Amazon Seller Central, to an industry-leading data destination like Amazon Redshift, Facebook Presto, Snowflake, Azure Data Lake Storage, Google BigQuery, and Amazon Athena.

Openbridge automates the processes of integrating with a data source, collecting, processing, cataloging, and loading data to a private, customer-owned destination.

Data Pipeline Examples

Our pipeline example will use a customer called "My Lifestyle." This customer uses Instagram for marketing, Google for paid search, Facebook for advertising, and Amazon for global e-commerce.

How many data pipelines will My Lifestyle need? First, they have five data sources;

  • Instagram Business

  • Amazon Seller Central

  • Amazon Ads

  • Google Ads

  • Facebook Marketing

Each data source has multiple profiles and accounts. These profiles and accounts for each data source will drive the number of data pipelines they will need. Here is the breakdown for each data source:

Instagram Business

  1. @mylifestylestore

  2. @mylifestylebranding

Amazon Seller Central

  1. mylifestylestore US

  2. mylifestylestore CA

  3. mylifestylestore MX

  4. mylifestylestore UK

  5. mylifestylestore DE

  6. mylifestylestore ES

Amazon Advertising

  1. amz-adprofile-US

  2. amz-adprofile-CA

Google Ads

  1. adwords-account-1

  2. adwords-account-2

Facebook Marketing

  1. brand-page-1

  2. brand-page-2

Each data source will require a data pipeline for each unique account, user, or profile. For example, Instagram Business needs two pipelines, one for "@mylifestylestore" and another for "@mylifestylebranding" accounts. Since these are two distinct Instagram accounts, they each need a separate data pipeline to a target destination.

My Lifestyle has six Amazon Seller Central stores. Each reflects a unique "mylifestylestore" store in six different countries (US, CA, MX, UK, DE, ES). This would be six data pipelines, one for each marketplace.

In total My Lifestyle will need 14 data pipelines for Instagram, Facebook, Google, and Amazon.

Connecting Your Own Data Tools

After we deliver the data, you are free to use an incredibly diverse array of tools like Looker, Tableau, Power BI, and many others to explore, analyze, and visualize data to understand business performance. Data ownership means you make the choices on how to apply business rules, models, or transformations with the tools that drive productivity.

Automated, Code-Free Data Pipelines

When we reference fully-automated, code-free data pipelines, we mean just that, there is no code. Our solution is a point and click, software-as-a-service platform for data pipeline automation. All we ask you to do is point us in the direction of the data source you want to collect data from and then tell us where the data should be delivered. That is it, we handle everything in-between via automation.

While there are some people who want to tinker with code under the hood, our solutions are centered on those that prefer not to. Everything we do is focused on efficient, easy-to-use, end-to-end automation.

The end result? While we are focused on delivering a robust platform architecture, data wrangling, and ops, your teams can focus on using data in ways that lead to better, faster decision-making.


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