Analytics and Data Science
Over the past few years, business intelligence has been the talk of the digital marketing town and we’ve seen more and more people discussing BigQuery as a means to data-driven marketing.
As a Google Cloud Platform Partner, our data engineers have been using BigQuery to make more from our client’s data for years, but we still get asked what are the advantages of using this cloud-based platform for businesses.
In this blog, we’ll look at some of the features BigQuery has and why these can benefit businesses.
BigQuery is a secure, serverless data warehouse that comes with a built-in query engine that can be used to store and query huge volumes of data in a very short amount of time. It is a fully managed, serverless architecture which means those using BigQuery can focus on gaining business insights, rather than the operation or infrastructure of the platform.
BigQuery is capable of running extremely advanced queries across huge, complex data sets, in a very short amount of time. However, rather than being reserved exclusively for large enterprises, BigQuery is a great platform for businesses of all sizes.
One advantage of BigQuery is that it offers a flexible pricing structure, meaning businesses only pay for what they use. Storage, and data scanning while running a query, are both billed separately – which makes BigQuery a cost-effective solution whether you want to just store your data, or if you want to query it too.
Unlike many large data warehouses, BigQuery still allows users to query their data using SQL rather than more complex syntax such as map-reduce. This means that, whilst the volume of data can grow almost limitlessly, querying the data is still accessible.
BigQuery users can create, train and call machine learning models within BigQuery using simple SQL via BigQuery ML. These models can then be run on the data sets stored in BigQuery, giving you advanced predictive analytics which can be used to inform your digital strategy.
BigQuery can integrate with Google Cloud’s machine learning platform, Vertex AI. We can also use it to call some models written in TensorFlow.
BigQuery has a Data Transfer Service, which allows you to set up a scheduled and fully managed automatic transfer of data from external data sources into BigQuery, including native integrations like the Google Marketing Platform and Google Ads, and external sources like Amazon S3. This gives users the ability to stream hit-level data directly into the data warehouse and interrogate, sort, and analyse this data.
Not only can this massively cut down on admin and ensure your data, and any analyses carried out, are fresh, it creates the opportunity to tie together different data sources for a holistic view of digital performance.
We are able to stream data into BigQuery as and when the data is available. This, paired with BigQuery’s ability to process data in seconds means the platform offers real-time analytics, allowing businesses to make decisions as and when the data highlights a need to.
As part of the Google Cloud Platform, BigQuery is an extremely secure data warehouse, meaning any data you store is protected. Administrators can control access to datasets by roles, groups, and individual users, making the data easily shared while remaining secure. There is also the option to grant access to view filtered data with users if a more granular look at certain datasets is needed.
BigQuery is an excellent platform which allows businesses to get actionable insights from their data, in real-time. While the platform itself is intuitive to use, working with data scientists and data engineers can help you get more from your data. Our team of data scientists and data engineers have the experience and skills required to utilise BigQuery’s advanced features and deliver bespoke solutions – get in touch and see how we can help.
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