[ Updated Mar 3, 2021 ]
If you’ve ever been involved in building and maintaining custom API connections between popular marketing/sales platforms and cloud data warehouses or data lakes, you’d probably agree that it’s a tedious process that always takes longer than originally estimated.
While building a simple API connection may not take a lot of your data team’s time, the problem is that the APIs of marketing platforms are updated frequently. And each update to your data source APIs means scheduled maintenance — and downtime — for your home-grown pipelines.
When you add up all the costs associated with your own data pipelines, it’s nearly never worth your time or investment. After all, why build something that you can buy for a fraction of the cost and effort?
And that’s why in this post, we’ll discuss the five main benefits of managed data pipelines. But before we get there, let’s quickly define what we mean with data pipelines and compare them to more traditional data integration.
What is a marketing data pipeline?
A marketing data pipeline, like Supermetrics, is a fully managed, no-code integration between your go-to commercial data sources (think Facebook, Shopify, Google, and Salesforce) and your storage, analytics, and reporting platforms (think data warehouses, data lakes, and BI tools).
To put it simply, a marketing data pipeline allows you to replicate any metrics and dimensions from your data sources into your cloud data platform of choice with a few clicks. That way, you can store all your marketing and sales data in one place.
Traditional data integration explained
In the past, the only way to centralize marketing data in a data warehouse or a data lake was to manually configure data transfers.
Let’s say an ecommerce company wanted to integrate their transactional data with paid media data to understand which channels and campaigns bring in the highest return on ad spend (ROAS).
In the not-so-distant past, they would have had to go through the following steps:
- First, they would need provisioned hardware such as an on-premise server, where they’d install a data integration software (such as Talend or Informatica).
- Next, they would configure the database to serve as a destination for the data.
- Then, they would build custom integrations using their ecommerce platform’s and paid media channels’ APIs, do data transformations, and push the transformed data to the database.
- After that, they would still need to validate the transfers, which typically takes a lot of trial-and-error, since the transfers should be built to withstand possible discrepancies.
- Finally, they would need to create a connection from the database to their reporting or business intelligence tool of choice.
As you can probably imagine, getting a stable data integration system up and running this way can take weeks — if not months. To add to the injury, each custom connection requires frequent maintenance to adjust for any changes in the source API.
5 reasons why you should start using a marketing data pipeline
Now that we’re all on the same page about the pain of configuring custom API connections, let’s look at the main benefits of managed data pipelines.
Data pipelines are sold as SaaS (software-as-a-service) products, which means that you’ll only pay for the subscription, while the data pipeline company takes care of everything else.
In fact, according to our calculations, you end up saving anywhere between 3–7X your data transfer budget with a managed data pipeline.
With Supermetrics, the price of your data pipeline depends on your data destination and the number of data sources you’re pulling data from. But unlike some of our competitors, we don’t charge for the volume of data you’re moving. This means that with Supermetrics, there’ll be no unwanted surprises in your invoices.
2. Lightning-fast deployment
Getting started with a managed data pipeline is quick. You don’t need to worry about installation, testing, or hardware configuration.
Since managed data pipelines use the cloud to handle large datasets and adjust to changes in data volumes, your computer won’t get exerted in the slightest.
3. Easy to learn
With legacy data integration tools, you would have needed to understand the solution architecture and learn how to implement the tools into your workflow.
With managed data pipelines, all you have to do is click around an intuitive user interface to select your sources, destinations, and set up your transfers. And since most data pipeline companies offer user-friendly documentation, anyone with basic computer skills can learn how to use them.
4. Support for ETL and ELT workflows
Data pipelines allow you to integrate data for different use cases. If you need readily transformed data for analytics, you can use ETL tools such as Google BigQuery. They make sure you can start analyzing your data in no time.
If you need untransformed data in its raw format, you’re looking for an ELT tool. These tools extract unstructured data and push it into the cloud storage bucket of your choice. The data stored in these buckets can then be transformed into further use in data warehousing, machine learning, and other data-intensive applications. Supermetrics offers cloud storage solutions to help with your ELT operations.
5. Unmatched security
Since building data pipelines is the full-time job of data pipeline companies, many of these tools have been built security-first. 9.9 times out of 10, you’ll end up with a more secure data pipeline by investing in a managed one rather than building your own.
For example, Supermetrics is SOC 2 compliant and we don’t store your data in our systems during the transfers. We simply encrypt your data at the source and decrypt it at the destination to make sure that no one can access your data during the transfer.
How to set up a managed data pipeline in 6 simple steps
Now that you know the main benefits of managed data pipelines, let’s look at how you can set up your first transfers in 10 minutes or less:
- Get a license for a data pipeline. (Psst! Most data pipeline companies — including Supermetrics — offer a free trial.)
- Authenticate access to your data sources. Typically, you can authenticate each data source with OAuth or single-sign-on.
- Select the datasets you’re looking to transfer and, optionally, the schema you’d like to use to guide the data extraction.
- Set your transfer schedule.
- Authenticate access to the destination of your choice — whether that’s a data lake (like Amazon S3, Azure Storage, or Google Cloud Platform) or a data warehouse (like Google BigQuery, Snowflake, or Azure Synapse Analytics.)
- Start your transfer.
With just these six steps, you can get data flowing within a few minutes.
Over to you
Getting data into the cloud used to require technical skills and a lot of time. With managed data pipelines, you don’t need a huge data team or months of uninterrupted time for building your custom connections. In fact, anyone from marketers to non-technical analysts will be able to set up data transfers in just a few minutes with a tool like Supermetrics.
But don’t just take our word for it. If you’re interested in seeing how quickly you can replicate data into your cloud data destination of choice, start a free trial of Supermetrics today.
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