Google

Google BigQuery

Composite Score

8.8 /10

CX Score

9.1 /10

79 Reviews Write a Review

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What is Google BigQuery?

BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. Use BigQuery to manage all data types across clouds, structured and unstructured, with fine-grained access controls. BigQuery's serverless architecture lets you use SQL queries to analyze your data. You can store and analyze your data within BigQuery or use BigQuery to assess your data where it lives.

Company Details

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Awards & Recognition

Google BigQuery won the following awards in the Analytical Data Store category

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2024 Emotional Footprint Champion

Latest Award, 2024

Service Experience
Contract Negotiation

Latest Award, 2024

2024 Data Quadrant Gold Medalist

2024

8 Top Rated Capabilities

4 Top Rated Features

2024

2023 Emotional Footprint Champion

2023

Service Experience
Contract Negotiation
Conflict Resolution

2023

2023 Data Quadrant Gold Medalist

2023

8 Top Rated Capabilities

6 Top Rated Features

2023

2022 Emotional Footprint Champion

2022

Strategy and Innovation
Service Experience
Product Impact
Contract Negotiation
Conflict Resolution

2022

2022 Data Quadrant Gold Medalist

2022

10 Top Rated Capabilities

5 Top Rated Features

2022

2021 Emotional Footprint Champion

2021

Google BigQuery Ratings

Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard to access more information on Google BigQuery.

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

88 Likeliness to Recommend

1
Since last award

97 Plan to Renew

1
Since last award

90 Satisfaction of Cost Relative to Value

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Emotional Footprint Overview

Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.

+90 Net Emotional Footprint

The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.

How much do users love Google BigQuery?

3% Negative

3% Neutral

94% Positive

Pros

Respectful
Acts with Integrity
Caring
Security Protects

Feature Ratings

Average 85

Data Management

Data Integration

Real Time Capabilities

Distributed Processing

Analytics and Data Science Tools

Data Security

Metadata Management

Platform Administration

Analytics and Reporting

Workload Management and Monitoring

Data Visualization

Vendor Capability Ratings

Average 84

Business Value Created

Vendor Support

Ease of IT Administration

Usability and Intuitiveness

Ease of Data Integration

Ease of Implementation

Quality of Features

Breadth of Features

Availability and Quality of Training

Product Strategy and Rate of Improvement

Ease of Customization

Google BigQuery Reviews

Beranice G.

Role: Consultant
Industry: Technology
Involvement: End User of Application

Validated Review

Verified Reviewer

Submitted Dec 2020

Effective Google Package.

Likeliness to Recommend

9 /10

What differentiates Google BigQuery from other similar products?

The capability on Big Data manipulations.

What is your favorite aspect of this product?

Getting used with the Google product even to the beginners is very simple.

What do you dislike most about this product?

Nothing at all to underline.

What recommendations would you give to someone considering this product?

I love the performance and the effective capabilities given to the user to easily deal with the complex data.

Pros

Helps Innovate
Continually Improving Product
Reliable
Performance Enhancing

George K.

Role: C-Level
Industry: Media
Involvement: Business Leader or Manager

Validated Review

Verified Reviewer

Submitted Dec 2020

Easy to Learn, A lifetime to master

Likeliness to Recommend

9 /10

What differentiates Google BigQuery from other similar products?

Breadth of community support and leadership in the analytics space. The ease of entry is a bit of a drug, once you start you soon find yourself knee deep in data and no way out. Its not a bad experience, just be prepared to grow.

What is your favorite aspect of this product?

Ease of data integrations and the cost management perspective. Very straightforward on the pricing and it truly delivers on the value.

What do you dislike most about this product?

IT / Devops administration component is fairly difficult to navigate with out a full immersion and depending on your team size could mean full time role.

What recommendations would you give to someone considering this product?

Plan your use of this tool in advance. Do not just jump in - even though it is easy to do so, reeling back from the precipice when you realize all you've put into this platform is difficult. Have a plan for access control and data lifecycle. Look at the catalog tools to help early on.

Pros

Continually Improving Product
Reliable
Performance Enhancing
Enables Productivity

Cons

Security Frustrates
Less Friendly Negotiation

Google BigQuery

What is Google BigQuery?

Company Details

Need Assistance?

Awards & Recognition

2024 Emotional Footprint Champion

2024 Data Quadrant Gold Medalist

2023 Emotional Footprint Champion

2023 Data Quadrant Gold Medalist

2022 Emotional Footprint Champion

2022 Data Quadrant Gold Medalist

2021 Emotional Footprint Champion

Google BigQuery Ratings

88 Likeliness to Recommend

1 Since last award

97 Plan to Renew

1 Since last award

90 Satisfaction of Cost Relative to Value

Emotional Footprint Overview

+90 Net Emotional Footprint

How much do users love Google BigQuery?

Pros

Feature Ratings Average rating of all product features, some of which may not be shown below

Data Management Includes data sharing, data storage, records management, and data security.

Data Integration Includes integration of data from multiple sources, merging systems, transforming data and capture data to form a unified view of a company's data assets

Real Time Capabilities Ability to analytics and visualize data as soon as it becomes available in underline systems.

Distributed Processing Data storage and processing is shared among many physical or virtual independents servers or sites for high volume data with seamless access to large datasets.

Analytics and Data Science Tools Includes Analytics and Data science components such as AI, statistical and machine learning libraries

Data Security Includes ability to hide sensitive data by masking with special characters or anonymous information.

Metadata Management Easily manage metadata associated with customer data or audience segments.

Platform Administration Includes back-end interface and administrative capabilities

Analytics and Reporting Includes historical & real-time dashboard visualizations, detailed & summary reporting and easy data extraction for data analysis.

Workload Management and Monitoring Includes task, performance, monitoring and time management

Data Visualization Thematic visualization with the ability to change views, including color, pattern/icon, dot-density, chart, scaled-symbol, and 3D prism themes

Vendor Capability Ratings Average rating of all vendor capabilities, some of which may not be shown below

Business Value Created Software needs to create value for employees, customers, partners, and, ultimately, shareholders. This data expresses user satisfaction - or lack thereof - with the product's business value.

Vendor Support The importance of vendor support will vary for each organization depending on internal capabilities, but there will always be issues that only the vendor can resolve.

Ease of IT Administration This data indicates whether IT personnel will be able to resolve issues and perform configurations efficiently and effectively.

Usability and Intuitiveness End user learning curves cost the organization money. Pay attention to your end users' technical ability to determine how important UX is in your purchase.

Ease of Data Integration Use this data to determine whether the product will cause headaches or make data integration easy.

Ease of Implementation Successfully implementing new software is necessary to realize its full value and promote end user adoption. This data indicates whether or not the product is easy to implement.

Quality of Features Feature quality is just as important as quantity. Use this data to determine if this product will do what you're purchasing it to do, easily, intuitively, reliably, and effectively.

Breadth of Features Users prefer feature rich software that enables them to perform diverse series of tasks. This data expresses user satisfaction with the product's breadth of features.

Availability and Quality of Training Effective and readily available training enables users to get the most out of the software you've chosen. Use this section to make sure your vendor's training programs and materials measure up.

Product Strategy and Rate of Improvement Vendors who don't stay on top of emerging needs and trends won't enable you to meet your business goals. Use this data to separate innovators from imposters.

Ease of Customization Don't get bogged down in a difficult customization; use this data to make sure you can easily achieve the functionality you need for your particular situation.

Google BigQuery Reviews

Beranice G.

Effective Google Package.

Likeliness to Recommend

Pros

George K.

Easy to Learn, A lifetime to master

Likeliness to Recommend

Pros

Cons

Most Popular Google BigQuery Comparisons

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1
Since last award

1
Since last award

Feature Ratings

Data Management

Data Integration

Real Time Capabilities

Distributed Processing

Analytics and Data Science Tools

Data Security

Metadata Management

Platform Administration

Analytics and Reporting

Workload Management and Monitoring

Data Visualization

Vendor Capability Ratings

Business Value Created

Vendor Support

Ease of IT Administration

Usability and Intuitiveness

Ease of Data Integration

Ease of Implementation

Quality of Features

Breadth of Features

Availability and Quality of Training

Product Strategy and Rate of Improvement

Ease of Customization