The key points you need to know about data warehousing for Ecommerce include:

  • Data warehouses aggregate and store Ecommerce data from many sources and make it available for business intelligence and analytics.

  • Data lakes, data lakehouses, and data marts are all variations of the traditional data warehousing model.

  • The benefits of data warehousing for Ecommerce include breaking down data silos, establishing a single source of truth, improving data security and privacy, and more.

The fate of Ecommerce businesses can rise or fall based on their decision-making and forecasting skills. By tracking the right metrics and KPIs (key performance indicators), Ecommerce stores can determine if their most recent marketing campaign or product launch was a massive success or an underwhelming disappointment—and if so, how should the organization correct its course?

In order to make the right decisions, however, Ecommerce companies need to efficiently access large amounts of data—everything from customer data to warehouse inventory levels. That’s exactly the role of a data warehouse in Ecommerce.

Data warehouses are large repositories for storing and processing big data, turning raw information into valuable insights. In this article, we’ll discuss the definition of a data warehouse in Ecommerce, as well as how Ecommerce companies can use data warehouses to streamline their workflows, perform business process optimization, improve the user experience, and more.

Table of Contents

What Is a Data Warehouse?

A data warehouse is a centralized repository for data storage and aggregation that contains information from a variety of data sources, making this information accessible to business intelligence and data analysis workloads.

Once inside the data warehouse, BI tools can mine your information for hidden trends, connections, and insights. Then, these tools will turn this raw data into dashboards, reports, and visualizations that are easily comprehensible to key decision-makers.

Data warehouses can be either on-premises or in the cloud. Some of the most popular cloud data warehouse solutions include Amazon Redshift, Google BigQuery, Microsoft Azure Synapse Analytics, and Snowflake.

Related Reading: What is a Data Warehouse and Why Are They Important?

For Ecommerce businesses, the different sources of data that go into a data warehouse may include:

  • Files (e.g., CSV files or Excel spreadsheets)

  • Database tables and databases, both relational (SQL) and non-relational (NoSQL)

  • CRM (customer relationship management) systems such as Salesforce

  • ERP (enterprise resource planning) systems such as Microsoft Dynamics 365

  • Ecommerce platforms such as Shopify

  • Social media posts and email campaigns

  • Analytics tools such as Google Analytics

To get all this information inside a data warehouse, Ecommerce companies need a data integration workflow. Data integration refers to the process of collecting information from multiple sources and collating it together in a single target location.

Traditionally, data warehouses have been paired with the ETL (extract, transform, load) approach to data integration. As the name suggests, in the ETL method, information is first extracted from one or more sources, transformed as necessary, and finally loaded into a destination. Users can define ETL data pipelines to run at scheduled intervals, ensuring that the target data warehouse always contains the freshest, most accurate information.

Related Reading: How to Integrate an Ecommerce Site

Before we move on, we should highlight several alternatives to a standard data warehousing solution. A data lake is a variant of the data warehouse for storing large amounts of data that have not yet been processed. This means that the information has entered the data lake directly, without first going through the transformation layer of ETL.

Data lakes are often used for storing semi-structured and unstructured data, such as text, images, and videos, that don’t fit neatly inside a traditional relational database schema. Another popular use case for data lakes is storing and processing high-volume, real-time data streams.

What if we could combine the data warehouse and data lake to get the best of both worlds? Enter the concept of the data lakehouse, which tries to offer both the structure of a data warehouse and the agility of a data lake. In a data lakehouse, a warehouse layer for data processing and analytics sits on top of the underlying data, which may be either structured or unstructured.

Finally, there’s the notion of a data mart, which is essentially a data warehouse on a smaller scale. Data marts are designed to hold information that is relevant only to a single team or department (e.g., sales reps or customer service agents). They are typically smaller in size than an average data warehouse and also draw from a smaller number of data sources.

4 Benefits of Data Warehousing in Ecommerce

We’ve defined what a data warehouse is—but why is it such an essential component of the IT environment for so many Ecommerce companies? Below are just a few benefits of using data warehousing in Ecommerce:

  • Breaking down data silos: A “data silo” is a repository of information that is available to only one team or department within an organization, even though other users could benefit from having access. Data silos often occur unintentionally, with the data owners not realizing that they could be preventing other employees from working at their greatest capacity. Data warehousing helps break down data silos by integrating information from across the business and collecting it in a centralized, easily accessible location.

  • Establishing a single source of truth: Many Ecommerce businesses struggle with data quality issues; for example, records may be duplicated in different locations. Even worse, two records might be out of sync or conflicting—forcing users to figure out which is the more up-to-date or accurate one. To solve this issue, a data warehouse can serve as a “single source of truth”: a centralized, widely accessible repository that acts as the official standard for enterprise data. This makes the process of data integration much easier: users can simply consult the "golden record" within the data warehouse, which is the most up-to-date version, rather than wondering if their local copy needs to be refreshed.

  • Improving data security and privacy: Ecommerce stores handle a great deal of sensitive information, including customer contact information and credit card numbers, that could be an appealing target for malicious actors. In addition, Ecommerce businesses may be subject to regulations such as the GDPR or CCPA that govern how they handle, process, and store this information. By keeping this information in a single centralized location—the data warehouse—it’s much easier for Ecommerce businesses to keep confidential data under lock and key than it would be if the data were scattered across different systems.

  • Boosting efficiency and productivity: For data scientists, gathering your Ecommerce data from across the enterprise is a tedious and time-consuming manual activity. One survey found that data scientists spend roughly 80% of their time on preparing and managing data, with only a small portion left for data analysis. With a data warehouse supported by an automated data pipeline, users can always be confident that the information they need for BI and analytics workloads is already present within the repository. This gives them much more time for higher-level revenue-generating activities, such as actually analyzing data and interpreting insights.

4 Use Cases for Ecommerce Data Warehouses

As we’ve discussed, there are many advantages to using a data warehouse in Ecommerce. But what does data warehousing look like in practice for Ecommerce businesses? In this section, we’ll go over four use cases for Ecommerce data warehouses.

1. Sales

Ecommerce sales teams need to manage their operations across a wide range of channels: emails, phone calls, social media, Google searches, online advertisements, and more. With this multichannel setup, where different team members focus on different specializations, it’s easy for data silos to occur. However, all of this omnichannel sales data must be integrated and analyzed to understand the team’s performance, both individually and in aggregate.

Using a data warehouse, Ecommerce sales teams can collect data from across these various sales channels and migrate it to a single location. They can then use this data as input to track crucial metrics and KPIs, evaluating which team members or techniques are excelling and which need improvement.

One common use case of data warehousing in Ecommerce sales is attribution modeling: a technique in which different touchpoints or channels are given credit for converting a prospect to a paying customer. Of course, attribution modeling heavily depends on the ability to integrate data across different sales channels and analyze it in aggregate.

For example, suppose that a lead initially finds your website through a blog post and then returns a week later to make a purchase after clicking on a Facebook ad. Attribution modeling is able to recognize both the blog post (which is labeled the lead’s “first interaction”) and the Facebook ad (the “last interaction”), ensuring that both channels receive credit for their role.

2. Marketing

Like their sales counterparts, Ecommerce marketing teams use a wide range of tools and technologies across different channels. These might include:

  • Ad platforms such as Facebook, Instagram, Pinterest, and Google

  • Website analytics tools such as Google Analytics

  • Ecommerce platforms such as Shopify, Magento, and BigCommerce

With so many initiatives to keep track of at once, marketing teams need a robust solution for handling the data generated by all of their campaigns—hence the need for a data warehouse.

A highly popular use case for data warehouses in Ecommerce marketing is customer segmentation. Marketing teams would like to separate the company’s user base into different segments and then target them with highly personalized campaigns to achieve a given objective. For example, customers who haven’t visited your store in a while might be lured back with a coupon code, while customers who purchased a given product might be interested in buying specific add-ons or accessories. Using a data warehouse makes it easy to slice and dice your customer data along many different dimensions, opening up new possibilities and opportunities for revenue.

3. Customer support

Ecommerce businesses may offer multiple support options for customers with questions and concerns, including phone, email, chat, forums, and knowledge bases. What’s more, a single customer may have contacts with several support agents across multiple channels, further complicating the issue of data integration.

Using a data warehouse for your Ecommerce customer service data is the perfect solution for stressed, overloaded customer support agents. Ecommerce businesses can set up data pipelines that pull together information from sources such as your CRM system, customer service platform, and call center software, as well as data on the customer’s transaction history and product delivery.

4. Predictive analytics

Thus far, we’ve only talked about the use of data warehouses for processing and interpreting historical data. But what about the ability to make better forecasts and predictions?

This activity is known as predictive analytics, and it can be applied to everything from next quarter’s sales to product recommendations for new customers. By compiling all of your information in a single place, data warehouses offer greater visibility into historical trends and data, so that you can extrapolate into the future.

For example, lead scoring is one of the most critical activities of your Ecommerce sales team, helping representatives determine which prospects to prioritize. Instead of relying on guesswork and gut feelings, you can use the information in your data warehouse to segment your leads along various dimensions (e.g., customer demographics or behaviors). You can then crunch the numbers to see which of these segments have been historically most likely to convert to paying customers and focus your efforts appropriately.

How Can Help with Ecommerce Data Warehouses

In this article, we’ve discussed the definition of data warehousing, as well as the benefits and use cases of a data warehouse for Ecommerce. Now the most important question is: how will you get your Ecommerce data inside your data warehouse?

For most Ecommerce businesses, the answer will come in the form of a dedicated data integration solution like The powerful, feature-rich data integration platform has been built from the ground up for the needs of Ecommerce companies. offers a simple, user-friendly, no-code, drag-and-drop interface. Everyone from your IT team to non-technical business users can take advantage of to define robust data pipelines from your sources to your data warehouse. What’s more, the platform includes over 140 pre-built connectors and integrations for third-party systems that Ecommerce companies use on a daily basis.

Unlike other integration solutions, uses a connector-based pricing model in which clients are charged based on the number of connectors in their data pipeline, not the amount of data they consume. This makes an ideal choice for growing Ecommerce businesses that expect to see their data consumption increase in the future. comes with a variety of features and functionality that fit the requirements of Ecommerce data warehousing. For example,’s FlyData CDC (change data capture) feature helps detect only those database records or tables that have been added or changed since the previous data integration job so that you don’t have to waste time and effort integrating the same information. also supports reverse ETL—i.e., migrating information out of a data warehouse and into third-party systems—which makes it easier and more accessible for non-experts to analyze and glean valuable insights.

Ready to learn about everything that the data integration platform can do for your Ecommerce business? Get in touch with our team of data integration experts today for a chat about your business needs and objectives or to start your 7-day pilot of the platform.