Python is one of the most beloved and powerful coding languages out there. With the adoption of Python for data science and data engineering tasks, the number of Python developers is growing at a huge pace. But Python sometimes is slow, so how can we find a solution for applications that need to fix a Python bottleneck in performance? Rust to the rescue!

More and more businesses are trying to leverage big data analytics to innovate and build new solutions, but unstructured, raw data doesn't provide proper insights. The answer? Intelligent cloud solutions.

Did you know that only 32% of companies report realizing tangible and measurable value from their data, and only 27% ​​say data and analytics projects produce insights and recommendations that are highly actionable?

Looking to level up your data-driven decision making? Machine learning and artificial intelligence models in GCP can help you predict the future.

Ricardo del Razo, CIO and Digital Transformation Leader at Grupo SADA, talks about the challenges and successes of adopting new processes, technologies, and delivery methods in the aftermath of the pandemic.

In our previous posts, we talked about how data warehouses and data lakes can help us manage our data in a more secure, cost-effective, reliable, and scalable way, as well as how to use GCP to improve our data pipelines and their orchestration. But it doesn’t matter how rich or robust your data structure is if you cannot use it to leverage your business decision making.

Spring Cloud Stream is a framework that helps developers with data integration problems, especially in event oriented applications. The goal of the framework is to make it easy to apply modern microservices architecture patterns, decouple application responsibilities, and port business logic onto message brokers.