Data is fantastic, but Big Data is even better. With big data, you get a broader scope of research, which ultimately goes a great way in informed decision-making. However, getting your hands on large datasets is not as easy as it seems. A myriad of factors come into play, making it extremely difficult for you to access such information. For instance, you need ample storage to host this data which is another expensive feat. Furthermore, you need analytics tools to run over the dataset and get accurate information. In fact, without credible analytic tools, you just have a bunch of information you cant make good use of. 

It is no secret that data is precious, and the more you have, the better. However, with extensive data comes several complexities that make a scientist’s job even more complicated. The future with Big Data may sound bleak, but that is not the case with BigQuery Public Datasets. With these tools, you can easily explore the world of open data. So what exactly are BigQuery Public Datasets

In this article, you will get to know about some BigQuery Public Datasets available for you to use. 

Introduction to BigQuery Public Datasets

In simple terms, a public dataset is any sort of dataset stored in Bigquery. It is then made available to users through the Google Cloud Public Dataset Program. You can then access these datasets and integrate them into your applications as you desire. It is worth noting that Google handles storage expenses for these datasets and allows access via a project. As the end-user, you will only be required to pay for the queries you perform on the data. You need only use SQL or standard SQL queries. You can access this information via the Cloud Console

For more information on the topic at hand, you can visit the BigQuery Public Datasets page. You will realize that there are over 40 public datasets available for you to utilize. Furthermore, there is a brief but comprehensive explanation of the datasets. This way, you can better understand the structure of the dataset before you begin the querying process. 

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5 Useful BigQuery Public Datasets

Below is the list of 5 useful BigQuery Public Datasets:

1) Google Trends 

BigQuery Public Dataset: Google Trend
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This is one of the essential BigQuery Public Datasets for businesses focused on reaching a specific Target Audience. By using the tool, companies stand to make better and more effective Data-Driven decisions. The difference between this dataset and the existing Google Trends UI is that it is more improved since it goes a long way in simplifying the manual experience with the mentioned platform. Some of the features that make the experience a whole lot easier include automated, aggregated, and indexed search data in BigQuery Public Dataset. 

For starters, it includes the top 25 stories and top 25 rising queries from Google Trends. Each of these is visualized as two separate BigQuery Tables where new terms are added daily. The list is updated for 30 days, which is the expiry period. Finally, users get Historical Data spanning five years spread out over 210 different locations in the US. 

2) American Community Survey (ACS)

BigQuery Public Dataset - ACS
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Like Google Trends, the American Community Survey (ACS) is another essential BigQuery Public Dataset that helps companies make informed decisions. This tool provides critical information regarding the American Population by contacting over 3.5 million households every year. The resulting information includes detailed demographic data across the US, which is categorized on various geographic levels. 

ACS benefits the E-Commerce sector as it is one of the most outstanding features in that it can be used as a component for Market Research. By querying the information in this dataset, businesses can make informed decisions about where most employees and customers are located. Furthermore, the data provides detailed information about the kind of customer base concentrated in specific areas. This way, businesses can decide what products and services are likely to appeal to this customer base. 

3) Google Community Mobility Reports

BigQuery Public Dataset - Google Community Mobility Reports
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It is no secret that COVID-19 has impacted every aspect of life, from businesses to education to travel. The Google Community Mobility Reports provide detailed insights on changes brought forth by COVID-19. Data is categorized based on region and the type of business. For instance, this BigQuery Public Dataset can provide valuable insights regarding changes in the retail industry. You can see how visits to areas such as parks and stores are changing due to the pandemic from the information provided. This BigQuery Public Dataset is especially useful for businesses that are planning to expand their reach to different locations. By querying available information, such enterprises get to learn how to adapt to changes in other regions. 

4) Google Analytics

BigQuery Public Dataset - Google Analytics
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This is one of the most valuable  BigQuery Public Datasets for Website Tracking. It provides you with real-time Metrics for any website you are tracking and allows you to compare two different datasets. Below are some of the key metrics you can get from the tool: 

  • Annual trends in the number of visitors, sessions, and page view year after year. 
  • A detailed breakdown of the devices uses to access the website. 
  • The total number of visitors, sessions, and page views

5) Census Bureau US Boundaries 

BigQuery Public Dataset - Census Bureau US Boundaries
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This is another critical dataset for businesses since it provides detailed Geographical Information for US regions. It includes boundary files derived from the TIGER/Line Shapefiles and other core Geographical materials from the US Census Bureau. This dataset can be used to answer critical questions such as the proximity of a particular area to amenities such as airports and sports stadiums. 

How To Use Public Dataset in Bigquery 

To use a public dataset in BigQuery, follow these steps:

  1. Sign in to Google Cloud: If you’re new to Google Cloud, create an account to evaluate how the products perform in real-world scenarios.
  2. Select or create a Google Cloud project: On the project selector page, make sure that billing is enabled for your Google Cloud project.
  3. Navigate to the BigQuery page: In the Google Cloud console, go to the BigQuery page to begin.
  4. Open a public dataset: In the Explorer pane of the BigQuery page, click +Add. In the Add dialog, search for public datasets, and then click Public Datasets to access datasets in the public project bigquery-public-data. This will provide you with the BigQuery public datasets list.

With this, you’ve seen how to add public dataset in BigQuery.

  1. Compose a new query: If the Editor field is not visible, click Compose new query. In the Editor field, you can enter your SQL query.
BigQuery Public Datasets compose query
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  1. Run the query: After composing your query, click the Run button to execute it and view the results.
  2. Clean up: To avoid incurring charges to your Google Cloud account for the resources used in this quickstart, you can delete the project, which will also delete any datasets or tables you’ve created.

Remember, Google BigQuery public datasets are available at no charge for storage, and you pay only for the queries that you perform on the data. The first 1 TB of data processed per month is free.

Here’s an example query you can run on a public dataset:

SELECT name, SUM(number) AS total
FROM `bigquery-public-data.usa_names.usa_1910_2013`

This query will retrieve the top 10 most common names from the USA Names dataset, which is part of the BigQuery open datasets

BigQuery Public Datasets quickstart query validator
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BigQuery Public Datasets query results ui
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The age of Big Data is here whether we like it or not. Therefore, it falls upon us to decide whether we will make use of the abundance of information. One of the most efficient ways is using BigQuery Public Datasets. You can answer almost any question by querying this collection of data. In case you want to export data into your desired BigQuery Data Warehouse, then Hevo Data is the right choice for you! 

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Orina Mark
Freelance Technical Content Writer, Hevo Data

With expertise in freelance writing, Orina specializes in concepts related to data integration and data analysis, offering comprehensive insights for audiences keen on solving problems related to data industry.

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