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.
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88 Likeliness to Recommend
1
Since last award
96 Plan to Renew
90 Satisfaction of Cost Relative to Value
Emotional Footprint Overview
+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
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Neutral
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Feature Ratings
Data Management
Data Integration
Distributed Processing
Real Time Capabilities
Analytics and Data Science Tools
Metadata Management
Data Security
Platform Administration
Analytics and Reporting
Workload Management and Monitoring
Data Visualization
Vendor Capability Ratings
Business Value Created
Vendor Support
Ease of IT Administration
Ease of Implementation
Usability and Intuitiveness
Quality of Features
Ease of Data Integration
Breadth of Features
Availability and Quality of Training
Product Strategy and Rate of Improvement
Ease of Customization
Google BigQuery Reviews
Ajay C.
- Role: Information Technology
- Industry: Finance
- Involvement: End User of Application
Submitted Jun 2023
Easy to use data warehouse
Likeliness to Recommend
What differentiates Google BigQuery from other similar products?
The ease of use , the performance of the product, the integrations capabilities with multiple data sources
What is your favorite aspect of this product?
As a part of implementing moden data stack using big query we have been able to produce data analytics solutions at a faster pace. The performance of the data source has been amazing and it was very easy to learn as well. The community support is the best. All the solutions can be found online.
What do you dislike most about this product?
None , it is an amazing product
What recommendations would you give to someone considering this product?
Amazing product with great capabilities
Pros
- Reliable
- Performance Enhancing
- Trustworthy
- Efficient Service
Viktor F.
- Role: Sales Marketing
- Industry: Finance
- Involvement: IT Development, Integration, and Administration
Submitted May 2023
great product!
Likeliness to Recommend
What differentiates Google BigQuery from other similar products?
ease of use
What is your favorite aspect of this product?
using row data
What do you dislike most about this product?
the time of loading of queries
What recommendations would you give to someone considering this product?
that is a really interesting tool that helps taking business to another level
Pros
- Helps Innovate
- Reliable
- Performance Enhancing
- Enables Productivity
Dominic C.
- Role: Sales Marketing
- Industry: Finance
- Involvement: End User of Application
Submitted Mar 2023
Effective and easily accessible cloud-based data
Likeliness to Recommend
What differentiates Google BigQuery from other similar products?
In our company, we were searching for a dependable and user-friendly cloud-based data warehousing solution. Additionally, its potential to integrate with other technologies was what drove the purchase. It was, in my opinion, a great tool for securely handling huge data queries and storing data in a warehouse.
What is your favorite aspect of this product?
Because BIgQuery is self-managed, it is highly straightforward to develop and build a data model without having to spend time allocating resources for every possible use case. Additionally, they provide a variety of price alternatives to meet diverse needs, protect data, and provide configuration options for appropriate governance.
What do you dislike most about this product?
But for us, Google Cloud BigQuery's scalability, cloud-native design, connection with other services on the Google Cloud Platform, usability, and quick query performance more than make up for these potential limitations. All the data was processed promptly using a secure method. Small problems are not a huge deal.
What recommendations would you give to someone considering this product?
Bigquery can be used in conjunction with SQL and allows you to express complicated reasoning in JavaScript. We utilize Colab to create rapid prototypes, and using Google Colab to connect to Bigquery was quite simple. Give it a try; its capabilities will let you operate more efficiently and save massive amounts of data in real-time.
Pros
- Helps Innovate
- Continually Improving Product
- Reliable
- Performance Enhancing
