Google BigQuery is a cloud-based data warehouse that offers many benefits over traditional data warehouses, including the ability to scale to petabytes of data, low pricing, and high scalability. In this article, we will discuss what BigQuery is, its features, and how it can be used to store and analyze data.
BigQuery is a data warehouse that uses SQL to store and analyze data. It has the ability to scale to petabytes of data, and it is priced low so that it is affordable for all businesses. BigQuery is also highly scalable so it can be used by businesses of all sizes. BigQuery has a number of connectors to data sources so that it can be used to connect to BI tools such as Looker Studio, Tableau, and Power BI.
What is Google BigQuery
In simple 2 words “Data Warehouse“. Big Query has the capability to store and analyze the data. And it does not require a credit card if you want to start with the analysis of the data.
There are over 100+ public datasets that you can use to analysis. Here is quick start video:
Why Google BigQuery
It’s heaven to those who run an online store, website, or digital marketing! There are inbuild connectors for Google analytics, Google Ads, Google Search Console, Youtube, and many other Google Products.
Apart from Google products and services, there are tools which will enable to transfer data from social media to Google BigQuery very quick and easy.
The BigQuery pricing is as follow:
|How BigQuery pricing works||BigQuery pricing is based on analysis type, storage, additional services, and data ingestion and extraction. Loading and exporting data are free.|
|Services and usage||Subscription type||Price (USD)|
|Free tier||The BigQuery free tier gives customers 10 GB storage, up to 1 TB queries free per month, and other resources.||Free|
|Analysis||On-demandGenerally gives you access to up to 2,000 concurrent slots, shared among all queries in a single project.||Starting at$5.00First 1TB per month is free|
|Monthly flat-rate commitmentBest for customers who prefer a stable cost for queries rather than paying on-demand.||Starting at$2,000for 100 slots per month|
|Annual flat-rate commitmentBest for stable cost for queries rather than paying on-demand. Save more with an annual commitment.||Starting at$1,700for 100 slots per month|
|Flex short-term commitmentPay for slots for 60 seconds, and each second thereafter until you delete or change your commitment.||Starting at$4.00for 100 slots per month|
|Storage||Active local storageBased on the uncompressed bytes used in tables or table partitions modified in the last 90 days.||Starting at$0.02Per GB. The first 10 GB is free each month.|
|Long-term logical storageBased on the uncompressed bytes used in tables or table partitions modified for 90 consecutive days.||Starting at$0.01Per GB. The first 10 GB is free each month.|
|Active physical storageBased on the compressed bytes used in tables or table partitions modified for 90 consecutive days.||Starting at$0.04Per GB. The first 10 GB is free each month.|
|Long-term physical storageBased on compressed bytes in tables or partitions that have not been modified for 90 consecutive days.||Starting at$0.02Per GB. The first 10 GB is free each month.|
|Data ingestion||Batch loading Export table data to Cloud Storage.||FreeWhen using the shared slot pool|
|Streaming insertsYou are charged for rows that are successfully inserted. Individual rows are calculated using a 1 KB minimum.||$0.01per 200 MB|
|BigQuery Storage Write APIData loaded into BigQuery, is subject to BigQuery storage pricing or Cloud Storage pricing.||$0.025per 1 GB. The first 2 TB per month are free.|
|Data extraction||Batch exportExport table data to Cloud Storage.||FreeWhen using the shared slot pool|
|Streaming readsUse the storage Read API to perform streaming reads of table data.||Starting at$1.10per TB read|
However, BigQuery pricing calculator is also available to use
Bring any data into BigQuery
Make analytics easier by bringing together data from multiple sources into BigQuery. You can upload data files from local sources, Google Drive, or Cloud Storage buckets, use BigQuery Data Transfer Service (DTS), Cloud Data Fusion plugins, replicate data from relational databases with Datastream for BigQuery, or leverage Google’s industry-leading data integration partnerships.
Learn more about third party transfer here.
Data warehouse migration
Solve for today’s analytics demands and seamlessly scale your business by moving to Google Cloud’s enterprise data warehouse. Streamline your migration path from Netezza, Oracle, Redshift, Teradata, or Snowflake to BigQuery using the free and fully managed BigQuery Migration Service.
Learn more on Migrate data warehouses to BigQuery
Gain a competitive advantage by responding to business events in real time with event-driven analysis. Built-in streaming capabilities automatically ingest streaming data and make it immediately available to query. This allows you to stay agile and make business decisions based on the freshest data. Or use Dataflow to enable fast, simplified streaming data pipelines for a comprehensive solution.
Learn more on Real-time analysis
BigQuery ML can help you build an e-commerce recommendation system, predict customers’ lifetime value, and design propensity to purchase solutions.
Analyze and gain deeper insights into your logging data with BigQuery. You can store, explore, and run queries on generated data from servers, sensors, and other devices simply using standard BigQuery SQL. Additionally, you can analyze log data alongside the rest of your business data for broader analysis all natively within BigQuery.
Marketing data warehouse
Marketing data warehouses let you deliver timely, targeted, and tailored advertising experiences that increase marketing performance. BigQuery offers seamless data connectors into Google Ads, Campaign Manager, and other marketing platforms for a holistic view of your business. Build advanced marketing audiences with Google Analytics and BigQuery’s built-in ML to drive higher ROI.
Free Analytics and 100+ public data sets to use from
To use BigQuery for free for practice, or analytical on Public dataset, you should read the blog on
How to Practice SQL on BigQuery for Free and watch the video: