BigCommerce to BigQuery 101 Simplified

As your BigCommerce Store starts to grow, it can be challenging to process the exponentially increasing data. Traditional on-premises databases become inefficient in effectively handling the rising data demands. A more economical and stable solution is opting for a Cloud Data Warehouse solution like Google BigQuery that provides On-demand scaling of both the storage and computing resources. 

Using BigCommerce’s native integration, you can easily transfer data from BigCommerce to BigQuery and take full advantage of its advanced & powerful analytics engine. This also allows you to leverage other popular data services available in the Google Ecosystem such as Google Data Studio.

In this article, you will learn how to seamlessly start replicating data from BigCommerce to BigQuery.  

Table of Contents

• What is BigCommerce?
  • Key Features of BigCommerce
• What is Google BigQuery?
  • Key Features of Google BigQuery
• Why Connect BigCommerce to BigQuery?
• How to Connect BigCommerce to BigQuery?
• Conclusion 

What is BigCommerce?

BigCommerce is a leading eCommerce platform that provides a complete package of tools to create and run an online store for your business seamlessly. Launched in 2009, BigCommerce is now assisting more than 60,000 business owners across 150+ countries. With a plethora of features available, you can design and customize your online shop and start selling your products globally in no time. You get complete control over your website and can perform various operations such as adding Products, Uploading Photos, Processing Orders, Creating Discount Coupons, Customizing Product Pages, etc.   

As this is a completely hosted service, you aren’t required to buy or manage web hosting. You can simply connect to the Internet, sign in to BigCommerce and start designing your eCommerce website. Keeping the interest of Developers in mind, you can also make tweaks in the CSS and HTML to personalize the website according to your style. BigCommerce offers a range of subscription-based plans that cater to the needs of both small and large-sized enterprises.

Key Features of BigCommerce

This SaaS platform is employed by various industries like electronics, healthcare products, jewelry, etc. Its huge popularity comes from the following eye-catching features:

• Manageability: From the beginning when you land on the BigCommerce Dashboard, clear instructions are provided to help you through the basics. Processing Orders, Managing your Inventory, and Updating your Stock Levels is a smooth process. The multi-currency support allows you to reach a wider audience and accept payments worldwide. You can even set rules for automatic tax calculation. With native integration for several destinations like Google BigQuery, you can easily transfer data from BigCommerce to BigQuery.
• Themes: BigCommerce offers a diverse collection of both free and paid templates. Using the Style Editor, you can customize these themes without any need for writing code. All of these themes are 100% optimized for all mobile devices providing the best customer experience.
• SEO: The Search Engine Optimization functionality of BigCommerce optimizes your website with improved loading speed and better ranks on the search engines. Following the most up-to-date SEO practices, it puts continuous efforts to improve your website UX. It provides you access to Metadata, Header Tags, Titles, URLs, etc for customization according to your content.  
• Marketing: With robust tools such as Mailchimp, HubSpot, iContact and Constant Contact you send Automated emails, Coupon codes, Discounts, etc. Through BigCommerce, you can also market on various Social Media Channels such as Facebook, Twitter, etc. With a fluid Google Adwords integration, you can promote your brand and products on Google also. The analytics tools help you keep a close eye on your business performance and provide deeper insights for making data-driven strategic decisions.    
• Customer Support: BigCommerce provides excellent 24/7 customer support via phone, live chat, and email to solve your queries. The subject experts analyze your inquiries and provide the best possible solution in short wait times. By opting for the Enterprise Plan, you get additional features with priority support. To know more the customer support, you can visit the BigCommerce Support Center. 

What is Google BigQuery?

Launched in 2010, BigQuery is a Cloud-Based Data Warehouse service offered by Google. It is built to handle petabytes of data and can automatically scale as your business flourishes. Developers at Google have designed its architecture to keep the storage and computing resources separate. This makes querying more fluid as you can scale them independently without sacrificing performance.

Since there is no physical infrastructure present similar to the conventional server rooms for you to manage and maintain, you can focus all your workforce and effort on important business goals. Using standard SQL, you can accurately analyze your data and execute complex queries from multiple users simultaneously.

Key Features of Google BigQuery

Google BigQuery has continuously evolved over the years and is offering some of the most intuitive features :

• User Friendly: With just a few clicks, you can start storing and analyzing your data in Big Query. An easy-to-understand interface with simple instructions at every step allows you to set up your cloud data warehouse quickly as you don’t need to deploy clusters, set your storage size, or compression and encryption settings.    
• On-Demand Storage Scaling: With ever-growing data needs, you can rest assured that it will scale automatically when required. Based on Colossus (Google Global Storage System), it stores data in a columnar format with the ability to directly work on the compressed data without decompressing the files on the go.
• Real-Time Analytics: Stay updated with real-time data transfer and accelerated analytics as BigQuery optimally allocates any number of resources to provide the best performance and provide results so that you can generate business reports when requested.
• BigQuery ML: Armed with machine learning capabilities, you can effectively design and build data models using existing SQL Commands. This eliminates the need for technical know-how of machine learning and empowers your data analysts to directly evaluate ML models.
• Optimization Tools: To boost your query performance, Google provides BigQuery partitioning and clustering features for faster results. You also change the default datasets and table’s expiration settings for optimal storage costs and usage.   
• Secure: BigQuery allows administrators to set access permissions to the data by groups and individuals. You can also enable row-level security for access to certain rows of a dataset. Data is encrypted before being written on the disk as well as during the transit phase. It also allows you to manage the encryption keys for your data.
• Google Environment: Maintained and managed by Google, BigQuery enjoys the easy and fluid integrations with various applications present in the Google Ecosystem. With little to no friction at all, you can connect BigQuery to Google Sheets and Google Data Studio for further analysis.

Why Connect BigCommerce to BigQuery?

For sending your data from BigCommerce to BigQuery, BigCommerce supports a native integration into Google BigQuery that enables advanced analytics and custom reporting. Connecting BigCommerce to BigQuery allows you to leverage the following benefits:

• Custom Reporting: With advanced analytics at your disposal, you can make custom reports such as “Revenue by Product Category”, “Revenue by Product Brand”, “Cost of Goods Sold”, and “Profit Margin”. You can also filter out your revenue by country, city, postal code, and more.
• Standard SQL: Once you sent your data from BigCommerce to BigQuery, you can write SQL queries to analyze your data.
• Business Intelligence: To visualize your data better, you can simply connect to various BI Tools such as Google Data Studio, Google Looker, Tableau, and Microsoft Power BI. 
• Single Source of Truth: BigQuery acts as a Central Repository for all your data coming from different sources and effectively analyzes massive volumes of data swiftly. 

Prerequisites

• This integration is supported for BigCommerce Pro and Enterprise plans only.
• BigCommerce allows only the store owner to access this integration by default. However, you can grant other users access by enabling the Manage Data Warehouses permission.
• Need to sign up for a Google Cloud account and set up the billing. 

How to Connect BigCommerce to BigQuery?

The native integration for transferring data from BigCommerce to BigQuery will automatically update your BigCommerce data in BigQuery at 10:00 AM UTC once per day. Also,  You can start sending your data from BigCommerce to BigQuery by following the simple steps given below:

• Step 1: Before moving ahead with the data transfer from BigCommerce to BigQuery, ensure that you have signed up for a Google Cloud Account. You may also opt for the free tier account that allows limited access to several Google Cloud products and services free of charge. A mandatory step for the BigCommerce BigQuery integration to work is to set up your Billing. You can do this by going to Billing > Overview in the main Google Cloud navigation console to get started. 
• Step 2: Now, you can start creating a Project. Click on the Navigation Icon in the top left of your Google Cloud Console Window. Navigate to IAM & Admin › Manage Resources & click on the Create Project option. You can now fill out a project name according to your convenience for replicating data from BigCommerce to BigQuery.
• Step 3: For creating a BigQuery Dataset, click on the Navigation icon present in the top left corner of your screen. Scroll down to the Big Data section and click on the BigQuery option. 
• Step 4: Go to the left side screen, and click on ” ⠇” option present next to the Project created in the above steps. Click on the Create Dataset Option and create a Dataset ID, for instance, using your domain name (like company.com).

• Step 5: In this step for loading data from BigCommerce to BigQuery, you have to set up the permissions for your Google Cloud Account. For that, navigate to IAM & Admin, choose your project present at the top of the page, and finally, click on the Add button. You can provide the following information.
  • New principals: bigcommerce@bc-data-production.iam.gserviceaccount.com
  • Role: BigQuery Job User

• Step 6: Navigate to BigQuery and choose your Project and open your Dataset. Go to Sharing › Permissions.

• Step 7: Now, click on the Add Principal button and add the following information for the BigCommerce to BigQuery data transfer:
  • New principals: bigcommerce@bc-data-production.iam.gserviceaccount.com
  • Role: BigQuery Data Owner

Once you have completed the above steps for setting up data transfer from BigCommerce to BigQuery, click on the Save Button. The above permissions enable you to start transferring data from BigCommerce to BigQuery account.

• Step 8: Go to your BigCommerce control panel and navigate to Advanced Settings › Data Solutions. Now, click on the Connect button present next to BigQuery under the Data Warehouses section.

• Step 9: Enter details of the project you created earlier for replicating data from BigCommerce to BigQuery i.e. your BigQuery Project ID and Dataset ID in the following format & then click on the Next option.
  • Project_name:dataset_name

• Step 10: After you have completed the basic steps for replicating data from BigCommerce to BigQuery, you can check if your project, dataset, and permission settings are configured correctly via the Test access button. In case your billing in your Google Cloud account is not set up, the test will be conducted in the “sandbox” mode and the test may fail.
• In case your test for the data loading process from BigCommerce to BigQuery fails in spite of the billing being already set up, you can do the following 2 things to rectify it and then click on the Next option:
  • Review your Project ID and Dataset ID and ensure they are formatted correctly.
  • Review your permission settings and ensure they are applied to the correct Project and Dataset.
• Step 11: Finally for completing the process to replicate data from BigCommerce to BigQuery, select your timezone and click on the Finish button. 

You will notice that the rows and your actual data will be filled in when the next scheduled data processing job runs. You can check the schedule for the data transfer from BigCommerce to BigQuery by going to Advanced Settings › Data Solutions in BigCommerce where the BigQuery status is listed. This completes the process to replicate data from BigCommerce to BigQuery.

Conclusion 

In this article, you have learned how to easily connect BigCommerce to BigQuery in easy-to-follow steps. BigCommerce’s native integration allows you to seamlessly transfer data from BigCommerce to BigQuery, allowing you to leverage advanced analytics and custom reporting capabilities. BigQuery enables you to execute standard SQL commands to analyze massive volumes of data efficiently. 

As you collect and manage your data across several applications and databases in your business, it is important to consolidate it for complete performance analysis of your business. However, it is a time-consuming and resource-intensive task to continuously monitor the Data Connectors. To achieve this efficiently, you need to assign a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse, BI Tool, or a destination of your choice for further Business Analytics. All of these challenges can be comfortably solved by a Cloud-based ETL tool such as Hevo Data.   

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If you are using Google BigQuery as a Data Warehousing & Analytics solution and searching for a no-fuss alternative to Manual Data Integration, then Hevo can effortlessly automate this for you. Hevo, with its strong integration with 100+ sources and BI tools (Including 40+ Free Sources), allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiffy.

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