Table of Contents

Our six key points on data pipelines include:

  1. Data pipelines are automated action sets that extract and transform datasets from various sources.
  2. Businesses that have multiple sources of data that need to be collected, analyzed and reported on require data pipelines.
  3. Data pipelines help ensure data accuracy while saving time by scaling data extraction and transforming processes through automation.
  4. There are multiple different types of data pipelines, such as cloud, on-premise, batching, real-time, open-source, and proprietary.
  5. When choosing a data pipeline tool, you should pay attention to how easy it is to set up, how many data connections are included, reliability, and the scope of additional features.
  6. Those with coding experience and resources can build their own data pipeline from scratch or trust the experts at Integrate.io and choose from hundreds of pre-built connectors.

Whether you’re a one-person show reselling items on an online marketplace or a large Ecommerce enterprise with hundreds of employees, these businesses share a common factor: both generate data. The size of your business can influence the amount of data you generate, sure. But any amount of data — if it’s not adequately accessible — is worthless.

Every business, especially an Ecommerce business, needs a data pipeline.

What Is a Data Pipeline?

Data pipelines move data from the source to a data warehouse. As the data moves through the pipeline, it’s transformed and perfected. The data arrives in the warehouse in a form that’s easy to analyze and derive business intelligence (BI) insights from.

A data pipeline isn’t a physical thing — instead, think of it as a virtual tunnel. Every time your organization creates a data point in one of your business tools (such as adding a new customer’s information to your customer relationship management [CRM]), that piece of information is suctioned (extracted) into that virtual tunnel. Given the parameters of the warehouse at the end of the tunnel, that data’s language is translated (transformed) into the warehouse’s language. This transformed nugget completes its journey through the virtual tunnel as it’s dropped (loaded) into the data warehouse. The data pipeline is the backbone of the extract, transform, load (ETL) framework. The data pipeline can take raw data, send it to a staging area for short-term storage, transform it, and then send it on to the destination’s reporting layer.

Integrate.io is a new ETL platform with reverse ETL capabilities and a blazing-fast CDC platform with deep Ecommerce potential. To get started on your own data pipeline, schedule an intro call today or shoot us an email for more information.

Why You Need a Data Pipeline

Your Ecommerce business probably has massive quantities of data. In fact, you might be surprised by how much data you generate. Analyzing that data requires a way to view all that data as one dataset.

Most of today’s online businesses have multiple tools, solutions, and services through which data flies every moment. A CRM tool, an accounting tool, a tool for keeping an eye on inventory levels, a tool for managing order fulfillment — the list is extensive. It’s not likely that all those tools are from the same company, so each solution was built differently, with different naming conventions, coding rules, and languages. All this data existing separately — while many of these tools have their own reporting functions — doesn’t show the big picture.

Remember high school algebra class? You couldn’t just add 3x + 2y + 4z — the languages (the variables) are incompatible. You had to do some fancy figuring to manipulate two of the three variables until you could solve for one…well, you get the idea. No need to induce high school math homework nightmares.

The same is true of your disparate datasets: their variables have to be manipulated and transformed into the same one, into the same language. The more datasets you have, the more complicated the process becomes.

This is why a data pipeline is crucial. It’s your calculator. It eliminates a majority of the manual calculations and process steps. It automates the flow of your data from its source, through the translator, and on to the warehouse, where it’s all English and easy to read, draw conclusions from, and run accurate real-time reports with. If your business does any of the following, you need a data pipeline:

  • Need real-time information to make business decisions
  • Store any of your data in the cloud
  • Have data in multiple source tools

Having all of your siloed data in one data warehouse ensures your data is consistent, and you can draw real-time conclusions at any time, contributing to your BI.

Key Elements of a Data Pipeline

Every data pipeline has three key elements: the source(s), the process steps, and the warehouse or destination.

  • The source. This is where all your data originates. Some of the most common sources are relationship management tools such as MySQL, CRMs like HubSpot, enterprise resource planning (ERP) programs such as SAP and Oracle, and data warehousing like Snowflake. Social media tools and Internet of Things (IoT) devices’ sensors can even be data sources.
  • Process steps. As data gets extracted from each source, transformed, and updated to fit your business’s needs, there are various steps, such as extract, transform, augment, filter, group, and aggregate.
  • The destination. After all the process steps, this is where the data is deposited. The destination can be a data lake, data repository, or data warehouse. Once data reaches the destination, it can be analyzed.

Are a Data Pipeline and an ETL Pipeline the Same Thing?

In a sense, yes. There are various types of data pipelines. An ETL pipeline is a type of data pipeline in that it transports the data from a source, manipulates and transforms it, and then dumps the data into the destination point, typically a data warehouse. But in the major sense of a data pipeline, an ETL system is normally just a process within the process of the overall data pipeline. ETL can be an automated subprocess within the pipeline or may not be a part of the process at all. A data pipeline, on the other hand, is a much broader term because it encompasses the whole process of moving the data along its journey.

An ELT pipeline simply reverses the steps of the ETL pipeline, which provides a fast data load that is then transformed into the necessary language and analyzed at the destination.

What Should You Look for in a Data Pipeline?

Some of the most important criteria when choosing a pipeline include:

  • Ability to continuously process large amounts of data
  • Should be as elastic and agile as the cloud
  • Have data processing resources that are both isolated and independent of anything else
  • Should democratize access to data and allow for self-management
  • Great availability
  • Disaster recovery protocols

What features do today’s data pipelines offer?

Today’s Data Pipeline Features

Modern pipelines provide multiple benefits for Ecommerce businesses, such as:

  • Easy access to business insights
  • Faster decision-making
  • Flexible and agile enough to handle peak loads

There’s an exhaustive variety of features that today’s pipelines offer, but let’s explore the five most important features you should look for in a data pipeline solution that can speed up and better inform your Ecommerce business’s decisions.

#1. Processes Data and Offers Analytics, Both in Real Time

This is number one for a reason. Real-time processing enables near real-time visualization and analysis, which means any decisions you need to make will have the most up-to-date information. The pipeline must be able to ingest a data flow from all your apps and tools with no delays, regardless of source, and quickly transform and load the data into its warehouse.

For instance, Integrate.io’s ETL tools and lightning-speed change data capture (CDC) make adding real-time changes effortless and are the heart of streaming real-time data. Real-time data integration processing is better than batch processing. Batch processing can take several hours or even days to perform all the motions, and by then, your systems have several hours or even days’ worth of new data. It can mean the difference between spotting a new trend or potentially malicious activity after it’s already too late.

#2. Fault Tolerance

Data pipelines can fail — it isn’t unheard of. It can happen during data transit. Because so much is riding on the processing of your data, modern data pipelines are extremely reliable, with near 100% uptime. This is thanks to distributed, fault-tolerant architecture that immediately notifies users if a node, application, or other service fails in the process. The fault tolerance is exhibited when, say, a node fails, and another node takes its spot with little to no intervening.

#3. Self-Managing

A modern pipeline uses tools with interconnectivity. Businesses can employ various solutions that automate data pipeline maintenance and, if needed, can be handled by the team. Data pipelines used to require time and effort, but this wasn’t manageable, as having to do things manually meant data bottlenecks and added complexity. Legacy pipelines often can’t handle today’s many versions of data, nor the speed at which it’s generated. But today’s data pipelines make a democracy of data access. It doesn’t matter what kind of data, where it comes from, or what language it’s in — businesses can use every bit of data they generate to inform future and in-the-moment business decisions.

#4. Processes Large Quantities of Data in Multiple Formats

According to Seed Scientific, there were 44 zettabytes of data worldwide at the beginning of 2020. While some data is already structured, 80% of business data collected is either semi-structured or unstructured, meaning today’s pipelines have to be able to handle large sets of JSON, HTML, or XML data (semi-structured) and other unstructured data such as log files or sensor information. The strength and viability of your big data pipeline matter to standardize, clean, enrich, filter, and aggregate data in near real-time.

#5. Streamlined Development

When pipeline development is streamlined, deployment is that much easier. Modifications and scaling can accommodate additional data sources whenever necessary. It’s easier to test a pipeline, too. When pipelines are built in the cloud, it’s possible to create test situations quickly by imitating the existing environment. A planned pipeline can be tested and modified before actually being deployed.

So, this is a lot of information to absorb. If you have questions about data pipelines, send us an email and we’ll be happy to walk you through your options.

How To Choose the Right Data Pipeline

The solution you choose ultimately depends on a variety of factors, not the least of which is how much data you churn out in a day’s time. When looking at the many options available, thinking about your business’s use cases, BI, analysis, and decision-making processes can help you answer these questions and inform your pipeline decision:

  • What kinds of data do you have?
  • How often should you extract, organize, and otherwise maintain that data?
  • How often should you update and refresh your data?
  • What kind of resources do you need to handle a pipeline and transform data? Do you have those resources? Can you get them?
  • What is your overarching goal for having access to your data? What metrics in your workflow do you hope to track that you’re not tracking now?

Another question that may or may not have entered your mind is: Can you just build your own data pipeline? Well, sure — you can. However, connecting the different sources with different languages will be tough on its own, but building a pipeline that can do that, that’s accurate, that you can sustain and scale…that’s challenging. And it probably seems a bit out of reach.

You might not have the coding knowledge or an in-house team with the ability to manage a project like that. But you’re not alone. A greater majority of businesses opt for data pipelines that are pre-built, and there are a lot of benefits to going this route. You get all the advantages of knowing it’ll work from the beginning and with the flexibility you need, without having to code anything yourself. But there are items you should think about when choosing a pre-built solution, too, such as these five points:

  • How easy is it to set up? Does your business have the resources necessary to create a pipeline from scratch? Or is it more feasible to put your resources into a pre-built data pipeline?
  • Does it offer interconnectivity? Does the pipeline you’re considering let you connect all your business’s tools?
  • Is it reliable? Will the pipeline you’re looking at be able to handle extracting and cleaning your business’s data without interruption? You count on this data to make the big decisions, and you can’t afford to have a solution break down in the midst of transformation or loading.
  • Does it save you time, energy, or money? Does the pipeline relieve some of the headaches from manually analyzing data? Does it inform your BI better than manual analysis? Does it cost less than what you’re already spending yet provide you with more bang for your buck?
  • Does it have all the features you need, and maybe even some you didn’t know you needed? Does the pipeline solution you’re considering require your business to invest in further solutions, such as additional APIs or data storage for staging? Or is everything you need, included in the pipeline service?

Knowing what you need and why you need it are important aspects of choosing the right data pipeline for your Ecommerce business.

Why Your Ecommerce Business Needs a Data Pipeline

You’ve got a business to run. You likely have accounting software, an inventory management system, and an order fulfillment tool, in addition to keeping tabs on your customers on social media channels, review sites, and more. Keeping track of all the data generated by each of those tools, even for a relatively small business, is tedious. For a business to be truly successful, decisions driven by data are the only decisions to make. Data pipelines are the foundation of your business intelligence and your reporting analytics. Housing and accessing all your data in one spot, formatted so that it can speak to other disparate data, means you can see the whole picture your data is ready to paint.

Manually extracting and merging data from disparate sources — even if only occasionally — is riddled with the potential for costly errors. Data-driven decisions require infallible data. Any insight you receive from error-filled data is worse than no insight. Investing in your business starts with investing in BI. The wealth you can unlock with the awareness of where your business actually stands can steer your business exponentially forward. Scalability begins with a data pipeline.

Integrate.io is a no-code ETL platform with reverse ETL capabilities, blazing-fast CDC, and deep Ecommerce capability that can take your collected data and turn it into actionable insights. If you’re ready for validation and to learn what a data pipeline could do for your Ecommerce storefront, schedule an intro call today.