A recent evaluation of Cloud Data Warehouse solutions from the experts at Forrester puts Google Cloud firmly in the Leader’s Quadrant. In fact, Google Cloud outscored other solutions when the evaluations of both its current offering and its strategy going forwards were combined.
According to the Forrester team, Google achieved this Leader status by delivering against three key areas.
Google Cloud simplifies data warehouse deployment and management. For Forrester, this means features like powerful automation capabilities for ingestion, query tuning, processing and data integration.
We know from our experiences with customers that you can get even complex data analytics projects into production in just a few weeks with Google BigQuery.
We also know that, no matter where your data is stored and how often you need to ingest it, BigQuery comes with tools — enhanced by an ecosystem of third-party providers like Fivetran and dbt — that let you quickly build robust data pipelines.
Google Cloud scales to match your needs. You want a solution that won't box you in, giving you plenty of room for future growth as you store and process increasing volumes of data and make it available to more users. At the same time, you want a solution that scales to match your current business needs, so you’re not paying for capabilities you’re not currently using.
Google Cloud has numerous customers storing and processing more than 100 terabytes of data and with more than 100 concurrent users. However, its consumption-based pricing model makes it very affordable for even very small companies who want to take advantage of powerful data analytics.
With its serverless architecture, it’s also no surprise that Forrester’s evaluation gives BigQuery top marks for performance and scalability.
3. Ambitious roadmap
It has a roadmap as bold as your own cloud ambitions. Most vendors are focused on simplifying their solutions to allow non technical users to access data directly. Forrester’s Leaders are looking to empower you to take the way you use data to the next level, allowing you to get the answers to the questions you really want to be able to ask.
For example, with BigQuery, you can create ML models using SQL queries and then execute them from within BigQuery itself, with no need to employ scarce ML or data engineering expertise. You can also tap into tools that let you easily get more out of geospatial data and unstructured data such as video, images and free text documents. Google is constantly adding new features and new tools that make it even easier for your business to become more data-driven.
Overall, Forrester concludes, ‘Customers like Google’s frequency of new data warehouse releases, business value, future-proof architecture, high-end scale, geospatial capabilities, strong AI/ML capabilities, good security capabilities, and broad analytical use cases.”
Working with our data analytics and AI team
Our Data, Analytics and AI practice brings together a highly committed team of experienced data scientists, mathematicians and engineers. We pride ourselves in collaborating with and empowering client teams to deliver leading-edge data analytics and machine learning solutions on the Google Cloud Platform.
We operate at the edge of modern data warehousing, machine learning and AI, regularly participating in Google Cloud alpha programs to trial new products and features and to future-proof our client solutions.
We have support from an in-house, award winning application development practice to deliver embedded analytics incorporating beautifully designed UIs. We are leaders in geospatial data and one of the first companies globally to achieve the Google Cloud Location-based Services specialisation.
If you'd like to find out more about how we can help you build your own modern data and analytics platform, why not take a look at some of our customer stories or browse our resources. Needless to say, please get in touch with our team if you'd like more practical support and guidance.