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.
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Real user data aggregated to summarize the product performance and customer experience.
Download the entire Product Scorecard
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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
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?
Pros
- Respectful
- Acts with Integrity
- Caring
- Security Protects
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
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
Google BigQuery Reviews
Beranice G.
- Role: Consultant
- Industry: Technology
- Involvement: End User of Application
Submitted Dec 2020
Effective Google Package.
Likeliness to Recommend
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
Submitted Dec 2020
Easy to Learn, A lifetime to master
Likeliness to Recommend
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
