Best BigQuery Analytics Tools

on Data Integration • November 9th, 2020 • Write for Hevo

BigQuery Analytics Tools

Are you looking for good BigQuery Analytics tools? We have you covered, this post acts as a guide to some of the best BigQuery Analytics tools available. Everyone knows how important data is. However, does having a ton of data have any meaning? Data is important but only random big data does not suffice business needs; data must be mined, processed, analyzed and stored to make it valuable. 

Thus, it is important to find a solution that can fulfil our needs such as storing huge data (might be in TBs or PBs) and analyze this huge data in reasonable time and get the desired result. Your search ends here, with Google BigQuery.

Google BigQuery is a highly scalable data warehouse solution to store and query data in a matter of seconds. This is fully managed by Google and can execute interactive queries.

Here’s a snapshot of what you will be looking at:

Why Google BigQuery?

  • We can perform interactive analysis on massive datasets such as TBs and PBs.
  • Query millions and millions of rows in seconds.
  • Supports a traditional SQL style query syntax.
  • Since BigQuery is a service (DAAS) we can access it by API call.
  • Data is redundant across the globe to make sure the availability of data all the time. 
  • ACL is in place to control the data access.
  • Scalable – Autoscaling to do the job in an efficient and faster way.
  • Stores hundreds of TB of data.
  • Most importantly pay for what you use.

Hevo Data: Load Real-Time Data in Google BigQuery

Hevo is a No-Code Data Pipeline. It supports pre-built data integrations from 100+ data sources. Hevo offers a fully managed solution for your data migration process. It will automate your data flow in minutes without writing any line of code. Its fault-tolerant architecture makes sure that your data is secure and consistent. Hevo provides you with a truly efficient and fully-automated solution to manage data in real-time and always have analysis-ready data in Google BigQuery.

Let’s look at some salient features of Hevo:

  • Fully Managed: It requires no management and maintenance as Hevo is a fully automated platform.
  • Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to transfer. 
  • Real-Time: Hevo offers real-time data migration. So, your data is always ready for analysis.
  • Schema Management: Hevo can automatically detect the schema of the incoming data and maps it to the destination schema.
  • Live Monitoring: Advanced monitoring gives you a one-stop view to watch all the activities that occur within pipelines.
  • Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support call.

Explore more about Hevo by signing up for a 14-day free trial today

BigQuery Analytics Tools

Data without visualization is not actionable and is also difficult to understand for non-technical users such as Business Analysts and other management people whose interest is to use the data instead of build the data or query the data.

This is where visualization or analytical tools come into the picture, there are a bunch of analysis and visualization tools available for free as well as on a paid subsription basis.

While there are several data analytics tools available for BigQuery, we will be looking at the following:

  1. Google Data Studio
  2. Power BI
  3. Visualization using Google Sheets

1. Google Data Studio

Data Studio is a visualization tool provided for free. We can connect any data source to Data Studio for reporting and visualization purposes. It works seamlessly with BigQuery and Google Sheets.

Benefits of Google Data Studio:

  • Free to use.
  • Can connect to any kind of data source starting from Google Sheets, LinkedIn, BigQuery, MySQL etc.
  • Can build customizable reports.
  • Supports real-time data integration.

Let’s get started with Data Studio:

  • Choosing template
  • Connecting data sources
  • Choose metrics that matter
  • Lastly, sharing reports

Let’s build a sample report on Data Studio using BigQuery data:

Step 1: Login to Google Cloud Console -> go to BigQuery -> select table to create visualization -> click on Export -> Export with data studio.

BigQuery Analytics Tools: Google Data Studio

Step 2: As per the requirement choose the chart, table, graph etc. we can select a predefined template, which fits our requirement.

BigQuery Analytics Tools: Google Data Studio

Step 3: We can share or integrate the report with other stakeholders and applications respectively.

After saving the report Share+ gets enabled click on Share+ -> add the appropriate stakeholders email ID to share with.

BigQuery Analytics Tools: Google Data Studio

Cons of Google Data Studio:

  • As of now report preview for mobile devices is not available.
  • Extensive data preparation is not available.

2. Power BI

Power BI is Microsoft’s Data Visualization tool used to convert data from various sources to interactive dashboards. Power BI has a bunch of connectors to connect with various data sources for visualization.

To create dashboard will need the following two products of Power BI:

  1. Power BI Desktop – to create dashboards
  2. Power BI Service- to analyze and view the reports.

Steps to connect and create dashboard in Power BI:

Step 1: Connect to BigQuery

File menu -> Get Data -> Database -> Google BigQuery

BigQuery Analytics Tools: Power BI
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Step 2: Select the BigQuery table or view.

Get data -> Google BigQuery -> Select Google Cloud project -> Dataset -> Table or View -> finally click on Load.

BigQuery Analytics Tools: Power BI

Step 3: Select the required visualizations and fields from the source table for analytics purposes.

BigQuery Analytics Tools: Power BI

Pros of Power BI:

  • Can be used for an extensive amount of data preparation.
  • Report preview is available for mobile devices.

Cons of Power BI:

  • The premium model is required to share the report.
  • Does not support Mac and Linux for report creation.
  • Data loading is slow with Google BigQuery.

3. Visualization Using Google Sheets

Google Sheets also plays an important role in ad-hoc reporting. Dashboards can be created using Google Sheets by integrating the BigQuery data into Sheets. Without logging in into BigQuery we can import data into a sheet and start building the dashboards.

Step-1: Connect to BigQuery from Google Sheet.

Go to Data menu -> Data Connectors -> Connect to BigQuery.

BigQuery Analytics Tools: Google Sheets

It will open the following window, you should select the required table and click on the Connect button.

BigQuery Analytics Tools: Google Sheets

Now start building the dashboard using table, graph, chart and functions.

BigQuery Analytics Tools: Google Sheets

Pros of Google Sheets:

  • Easy for access control
  • Support collaborative editing 
  • Compatible with Microsoft Excel

Cons of Google Sheets:

  • Limited visualization options
  • Not possible to unite the different data sources

Conclusion

There are a number of visualization tools available with its own advantages and disadvantages, so based on the use case, you can choose your best fit.

Hevo Data is a No-code Data Pipeline. It supports pre-built integration from 100+ data sources. You can easily migrate your data to Google BigQuery in real-time.

Explore more about Hevo by signing up for a 14-day free trial today.

Share your experience of using any of these Google BigQuery Analytics tools in the comment section below.

No-Code Data Pipeline for BigQuery