Item: Google BigQuery
Rating: 6
Author: Verified User

Use Cases and Deployment Scope

We use Google BigQuery in conjunction with Bloomreach, this allows us to query the back end of the data without having to use the front end. The tool is fast to run queries and allows us to move the data to our other Data Warehouse environments quickly with little effort.

Pros and Cons

Fast Query Engine
Useful Documentation
similar syntax to SQL server

UI - its not the nicest UI
Original setup can be challenging
Depending on how you use it can become expensive

Return on Investment

Ability to return data via our ETL process
hit the deadlines of returning data

Alternatives Considered

Microsoft SQL Server, Azure SQL Database, Azure Synapse Analytics and Amazon Redshift

Google BigQuery i would say is better to use than AWS Redshift but not SQL products but this could be due to being more experience in Microsoft and AWS products. It would be really nice if it could use standard SQL server coding rather than having to learn another dialect of SQL server. It was choosen due to the 3rd parties choice of software.

Key Insights

Do you think Google BigQuery delivers good value for the price?

No

Are you happy with Google BigQuery's feature set?

No

Did Google BigQuery live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Google BigQuery go as expected?

I wasn't involved with the implementation phase

Would you buy Google BigQuery again?

No

Other Software Used

Amazon Redshift, Amazon S3 (Simple Storage Service), Amazon EventBridge, Microsoft Power Automate, Microsoft Power BI, Microsoft Excel, Miro

Likelihood to Recommend

Google BigQuery handles big data sets really well and has a solid enginge to query and maniulapte the data. The syntax is easy to pick up if your use to other database languages like SQL server but there are some syntax differences. Once setup it is a simple product to use and utilise

Users and Roles

3 - The data team are the only uses of this tool within the organisation due to Google BigQuery being used as an addition to the current AWS Redshift Data Warehouse and is used due to it being the choice of product by the 3rd party supplier, Looking to expand this maybe in the future to the Report Development Team.

Support Headcount Required

5 - The main support required was to setup Google BigQuery which was done by the IT team, The data team use the product on a regular basis and an ETL moves the data from here to the main DWH. The main skill required other than setup for this product is either experience in Google BigQuery or at least experience in TSQL language is a big benefit.

Business Processes Supported

ETL Process Movement
Debugging Front End Movement
Data Storage even when removed from front end

Innovative Uses

Used in ETL process
Used in Conjunction with Python
Intergrated into Bloomreach reports directly

Future Planned Uses

Use it for Predicitive Analytics
Use to monitor usage of users
Expand Usage to other teams in the business

Likelihood to Renew

7

We have to use this product as its a 3rd party supplier choice to utilise this product for their data side backend so will not be likely we will move away from this product in the future unless the 3rd party supplier decides to change data vendors.

Products Replaced

No

Average product and does what it says it can

Overall Satisfaction with Google BigQuery