The Cost of Building Your Own Google BigQuery Data Warehouse for PPC Data

Google BigQuery is an excellent data warehousing solution for digital advertisers and agencies looking to launch their own robust data infrastructure to store, analyze, and transform their PPC data. The search engine/advertising giant recognizes the power in providing its customers with a powerful solution to house all of their marketing data.

Not only is generating a Google BigQuery cloud project and data warehouse straightforward and quick, but they offer free built-in data pipelines to and from their most popular platforms (Google Ads, Google Analytics, Google Data Studio, Google Sheets) to help you get the data you need. While a data warehouse novice can generate a Google BigQuery data warehouse fairly easily, that doesn’t mean building the infrastructure to aggregate, store, and query all your data is simple.

Although you can send as much data to Google BigQuery as you want, Google BigQuery charges for data storage and data queries. If you’re managing your own PPC data warehouse, there will be upfront and hidden costs you may incur simply by how data is set up to flow into tables or how you access it after it’s stored. We’ll highlight some common reasons why your Google BigQuery data warehouse may be accumulating more costs than you expected and how to prevent it moving forward.

What is Google BigQuery?

BigQuery is an enterprise data warehouse solution that makes it feasible for businesses to store and query massive data sets by using the processing power of Google’s cloud infrastructure.

Most notably, BigQuery enables super-fast SQL queries. BigQuery is so powerful that it’s used by Google’s own teams (internally known as Dremel) to analyze data across their own services such as Google Search and Gmail. BigQuery can process 35 billion unindexed rows of data in tens of seconds and is perfect for digital advertising agencies to analyze massive quantities of their clients’ marketing data.

Why is Google BigQuery Great for PPC Data?

A key component of almost every digital advertiser’s job is to aggregate PPC performance data, analyze it, and report on it to stakeholders or clients. For advertisers who run campaigns across multiple platforms and/or for multiple clients, aggregating all the PPC data needed to run such analyses and reports becomes impossible to scale over time.

Google BigQuery simplifies PPC data aggregation, storage, and analysis.

For digital advertisers running campaigns on Google Ads only, Google BigQuery offers a built-in connector. It takes a few clicks to get Google Ads data flowing into your own PPC data warehouse. There are 80+ tables that break Google Ads performance data down into segments that you can use to uncover insights.

While Google doesn’t offer built-in connectors for non-Google ad platforms (Microsoft Ads, Facebook Ads, LinkedIn Ads, Twitter Ads), there are plenty of solutions to get cross-platform data into BigQuery as well. As we’ve walked through in “How to Transfer Facebook Ads Data into Google BigQuery”, you can import data manually, use a data pipeline such as Funnel or Improvado, or use Shape Advertising Data Infrastructure.

Each option has it’s pros and cons (manual/DIY - PPC data pipelines - ADI), so finding the right option really comes down to how much work you want to do to build and maintain your PPC data warehouse. Google BigQuery is so powerful because it allows you to store all your current and historical PPC data together in one platform. You can run analyses on data directly in Google BigQuery or port your data out to powerful reporting and BI tools to generate more robust PPC performance detail.

What’s Included Free with a Google BigQuery Data Warehouse?

When using a Google BigQuery data warehouse, you assume costs for data storage (housing all the historical and current PPC data you need) and querying data (running analyses to uncover performance insights).

If you sign up for the Google Cloud Free Tier, you receive a limited amount of data storage and queries for free for 90 days. This allows you to try out building and operating your own Google Data Warehouse and get a feel for the power of the solution. You can store up to 10 GB of data per month for free. Likewise, you can query 1TB worth of data per month for free as well.

There are a number of free operations or tasks such as loading data into Google BigQuery, exporting data out of Google BigQuery, or copying data tables that do not cost you any additional money. Rather, you’re simply charged for the storage and querying of the data you load or copy.

What’s Not Free with a Google BigQuery Data Warehouse?

Assuming you signed up for the Google Cloud Free Tier, you will start accumulating storage and querying costs after the 90-day free trial period.

At the highest level, costs for a BigQuery can be broken down into three simple areas:

  • Active Storage Costs: Fee assumed monthly for data stored in BigQuery that has been modified in the last 90 days.
    Cost: $0.020 per GB (for any data stored above 10GB free each month)

  • Long Term Storage Costs: Fee assumed monthly for data stored in BigQuery that have not been modified in the last 90 days.
    Cost: $0.010 per GB (for any data stored above 10GB free each month)

  • Data Queries Cost: The cost to run queries against data you have stored in Google BigQuery
    Cost: TBD determined by query pricing model used

While storage costs are relatively upfront, you may run into some confusion or unexpected costs with queries. Queries can be charged using on-demand pricing, hourly, with a monthly flat rate, or an annual flat rate. What you choose as best for your business will depend on the number and complexity of the queries you run on your PPC data, how many people or systems are utilizing that data, and if you are increasing/scaling the data you store and query over time.

Use these links to find more detail on Google BigQuery pricing and quotas/limits, or try the Google Cloud Pricing calculator to learn more.

Are there any hidden costs of Google BigQuery?

Google does it’s best to provide transparent pricing documentation, a cost calculator, and a real-time billing dashboard so you can understand data costs before your business is charged. That being said, if you’ve never built or managed your own data warehouse before, be sure to pay attention at this stage. Figuring out the right way to structure your data warehouse so that you’re not storing data unnecessarily or having to run multiple giant queries to get the information you need is important. If you don’t put the right user controls in place, you may find that having multiple people at your organization running data queries could cause your PPC data warehouse costs to accumulate faster than expected.

One other thing to monitor is how the tools you connect to Google BigQuery may affect your pricing. While it’s free to transfer data to Google Data Studio (as noted above), as Alex Danilin (Lead Product Manager at found out, tools like these can impact pricing. He connected Google BigQuery to Google Data Studio and wrote a custom query to only pull a portion of his data into his Data Studio reports. Data Studio made a bunch of separate queries instead of one aggregate query, meaning he was charged multiple times over for queries on the same data set.

How Solutions like the Shape ADI Solves These Problems

For digital advertisers or agencies without extensive data warehousing resources/knowledge or engineering teams, building and managing a Google Cloud data warehouse may be a scary prospect. Scaling a usable data warehouse requires building out API integrations with each ad platform or implementing a data pipeline software. Creating a foundation to store and normalize all your PPC data together, then managing the data warehouse in perpetuity requires someone with experience in these fields. All this needs to be done while and ensuring you do so in the most cost-efficient way possible.

Shape’s ADI eliminates all the headaches and hassle of building and maintaining your own PPC Data Warehouse. Our team has identified the common roadblocks detailed in this article while building our own PPC software over the years and put that knowledge into the Shape ADI.

With a few simple steps, the Shape ADI generates a fully managed PPC data warehouse that can store historical and current PPC data across seven ad platforms. PPC data is normalized, meaning you can pull cross-channel analyses using a single ADI table, or you can segment data more deeply for an individual ad platform.

Since the ADI includes a fully-managed data warehouse, your company never has to devote resources to maintaining infrastructure or API integrations.

But best of all, with a Shape ADI, you don’t pay for variable storage or query costs. You pay a single monthly fee for your ADI (a two-way API, a fully-managed Data Warehouse, and public connectors to your favorite reporting and BI tools). Shape assumes any costs associated with scaling your data storage or querying needs.

Simplify Your PPC Data Warehousing Costs with Shape’s ADI

Have all your company’s PPC data at your fingertips with Shape’s Advertising Data Infrastructure. Give your teams access to robust cross-channel PPC data, a two-way API, and a powerful data warehouse, without worrying about the bill.

Interested to learn more about what companies like yours have already built with a Shape ADI? Don’t hesitate to schedule a free consultation with our team today before diving in.

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