Faster Analytics And Smarter Data In The Cloud
Limitless data storage, secure and accessible data to globally distributed teams, and dynamic processing of large data sets in real-time.
They’re only a few of the benefits linked to moving to a cloud-based data warehouse.
Get the most out of your data warehouse modernisation with Google Cloud
Smarter data insights in shorter cycles
with Google BigQuery
As the cornerstone of Business Intelligence, BigQuery permits uninterrupted data transformation, integration and analysis. Get your projects up and running in virtually no time. Modernise your data infrastructure with Google’s proven migration methodology & our services.
Modernise your infrastructure & optimise costs
with ML in BigQuery
Streamline your workloads and run analytics with the ML-powered BigQuery.
See as much as up to a 52% decrease in your TCO.
Secure your data in Google Cloud
Trust Big Query’s next gen cybersecurity infrastructure to keep your data safe.
Smooth migration with no downtime.
Benefits of data warehousing with BigQuery
Discover the power of BigQuery, Google Cloud’s data warehouse platform.
Foundation for AI
Build & operationalise ML models directly within your data warehouse with BigQuery ML. Train powerful models on structured data with Cloud Machine Learning Engine and TensorFlow integration.
Reduce the need for code rewrite & provide advanced SQL features with a standard ANSI:2011 compliant SQL dialect – supported by BigQuery.
On-demand or flat-rate pricing models available for you to choose the pricing that fits you best.
Serverless data warehousing
Get the resources you need, when you need them. Skip the overhead of infrastructure or system engineering.
Real-time & predictive analytics
Stay up to date with your business & predict business outcomes, in real-time. Meet BigQuery’s high-speed streaming insertion API, which ensures a powerful foundation for real-time analytics.
Lower TCO than cloud data warehouse alternatives
Benefit from a 26%–34% lower three-year TCO than Cloud data warehouse alternatives.
Trust & Data Protection Guaranteed
Ensure security, governance and reliability with BigQuery’s controls and default data encryption.
Access data & share insights easily
Securely access and share analytical insights in your organisation with a few clicks. Add beautiful data visualisation on top of it with BI tools like Looker. Work with Devoteam G Cloud to accelerate your data warehouse modernisation journey.
Get to insights faster with our data & analytics accelerator
Accelerate your data warehouse modernisation up to 3x with Flycs. Concentrate on what really matters: the business insights.
Speed up your data & analytics projects up to 3x by automating repeating processes like config management, versioning, orchestration, etc.
Replicate with consistency
Standardise structures & processes and replicate data & analytics projects across your organisation.
Easily ensure data governance.
Get an out-of-the-box top notch DevOps ecosystem for your data & analytics projects.
This includes deployment stability, readable declarative code, fast iteration, fully managed CI/CD, Infrastructure-as-code & more.
“We really wanted to be prepared for the future in the way we’re doing data analytics. With a lot of flexibility and the use of new technologies.”
Our partner Services
Technical Analytics Design Document
An implementation blueprint created in the pre-study phase with customer stakeholders.
Key points covered in this document are.
Data Warehouse outline.
Data Warehouse and ETL
The ETL pipelines are tested and delivered along with the Data Warehouse. Additionally, the ETL pipeline should be scalable. Included in the delivery is the CI /CD for ETL and Schema changes of the Data Warehouse. The Data Warehouse will be reconciled against the previous data warehouse and signed off by the customer.
Any functional visualisations on the previous data warehouse will be migrated over to the new data warehouse and also reconciled to ensure that the reports show the same results.
The implementation of Looker may also be included in this deliverable, along with the relevant best practices.
Cost optimisations on BigQuery will be conducted after the usage of the new data warehouse.
Suggestions such as converting to a flat-rate plan may be warranted if usage matches the need.