BigQuery appears to be the hot buzzword in many enterprise-level marketing, analytics, and consumer insights circles right now. What’s not readily apparent to many organizations, though, is how they should actually be using BigQuery to drive their data engine forward.
To better understand how Google’s BigQuery platform can possibly help your company, let’s first start with the basics—what in the world is BigQuery, really?
The simplest definition comes from Google itself: “BigQuery is Google’s serverless cloud storage platform designed for large data sets.”
Now let’s unpack this to provide some actual clarity. “Serverless” means storing your data cheaper and scaling it faster. BigQuery can handle a lot of data very fast and at a low cost. The platform is there to help you get all of your data in one place for faster insights, which leads to faster results.
Other helpful BigQuery benefits include:
- Built-in integrations that make building a data lake in BigQuery simple, fast, and cost-effective.
- Centralizing your data to allow for auto-integrations with Google Cloud’s machine-learning tools for advanced data science reports.
- A one-click integration with Data Studio means visualizing processed tables is simple and fast.
- ETL solutions like DataFlow and DataProc that take the overhead out of data transformation.
Now that you have a high-level understanding of BigQuery, let’s take a deeper dive into some of these uses.
Integrations with Google Sheets and Analytics 360
From any query, you can choose to extract directly into Google Sheets, allowing you to explore your data at anytime with one click of the button. If your team wants to get hands-on with data, but doesn’t have the SQL skills to write complex queries, they can simply export any table to Sheets and get to exploring. Analytics 360 can in fact be integrated with BigQuery with a single click, allowing for hit-level analysis and more. Exposing the raw hits in BigQuery allows for advanced analytics reporting, and it’s one less platform you have to put into your data lake (because Google does it for you!).
Data Lakes Made Simple
It’s time to get all your marketing data, analytics data, and operational data in one place. BigQuery is a product designed for taking on a huge amount of data at very low cost. That makes it perfect for storing large amounts of raw data. What’s more, dataset and table creation can all be done quickly through the interface. If your platform doesn’t have a BigQuery integration, there are pre-build code libraries for integrating custom data sources. The libraries make building the data lake quick and reliable. The Google Cloud Platform comes with a number of solutions to help get your streaming data, SQL data, and file-based data into BigQuery without having to write custom code.
Data Science and Machine Learning
Storing your data lake in BigQuery gives you an auto-integration to Google Cloud Console’s suite of artificial intelligence and machine-learning tools. This allows you to carry out advanced data analysis, such as customer lifetime value. You can use these products with your data to start predicting data points such as future revenue or product pairing. Google Cloud Console lets you access your BigQuery data in Compute Engine and other server solutions where you can run processes in the cloud without having to pay for expensive machines. Having your data stored within the same system that does your cloud computing keeps you from consuming all your network traffic while transferring large datasets around—making big data fast and cheap.
Low-Effort, ‘Sexy’ Dashboarding with Data Studio
BigQuery makes visualizing your data a high priority. So much so, in fact, that they put a button right on your tables that takes your straight to Data Studio, where you can start aggregating and visualizing your data points in seconds. There is no need to set up database configurations or deal with VPNs. Google took out all the steps between storing the data and visualizing the data to get you faster visualization. Data Studio is not only accessible from any BigQuery table, but also allows you to customize your reports to your brand, making them both “sexy” and valuable.
DataFlow and DataProc make processing tables simple
If your data needs to be processed before it can be stored, you need an ETL solution to process your data in an automated way. ETL (extract, transform, load) is a system that will read, process, and load your data into any source. Google Cloud Console’s DataFlow and DataProc are two ETL solutions that connect natives into BigQuery. DataFlows Apache Beam and DataProcs Hadoop help distribute processing for streaming and stored data so you can set up your data pipes and never touch them again. No matter how complex the data, Google’s ETL solutions will help you process your data into BigQuery to make storing data simple.
Learn More about BigQuery
If you have more questions about BigQuery and how it can be utilized to help your organization, reach out to the Google Marketing Platform Certified Partners at InfoTrust today.