Systems | Development | Analytics | API | Testing

When doing long-term planning for an organization, it is really helpful to start with a statement of what the architecture is and what that architecture will encompass. The architectural definition of the technology that will be used will serve as a long-term guide for making technical decisions. In addition, a properly built architecture serves as an instrument of focus, direction, and prioritization for the organization.

When you’re racing around a circuit at over 200mph, there isn’t much room for error. There's a team of thousands backing you, millions of dollars on the line and a grid of other teams vying for the podium. In motorsport, every millisecond counts – and that’s where data can make the difference. This is what I spoke to Joe DosSantos about in the latest episode of Data Brilliant.

Cross-cloud analytics are critical to breaking down data silos. Moving data with usability, security, low-latency, and audibility makes it a reality.

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. For analytic applications to properly leverage a hybrid, multi-cloud ecosystem to support modern data architectures, data observability has become even more important. I spoke to Mark Ramsey of Ramsey International (RI) to dive deeper into that last subject.

Learn how Fivetran solution architects are supporting customers with implementing robust and scalable data platforms.

Use new BigQuery geospatial functions ST_IsClosed and ST_IsRing

Zeotap is a next-generation Customer Data Platform hosted in Google Cloud aimed at building customized Audience segments and activating at scale.

According to IDCs Global Datasphere, 64.2 ZB of data was created in 2020 alone. This number is projected to grow by 23% annually from 2020-2025. Therefore, we need data governance frameworks for efficient data management and control. This will help us extract maximum value out of such high volumes of data. Such frameworks would be required for data integrity, data protection, and data security. Indeed, according to BDO, the average data breach cost has been estimated to be around USD 3.8 million.

ClearML is an open source MLOps platform, and we love the community that’s been growing around us over the last few years. In this post, we’ll give you an overview of the structure of the ClearML codebase so you know what to do when you want to contribute to our community. Prefer to watch the video? Click below: First things first. Let’s take a look at our GitHub page and corresponding repositories. Later on, we’ll cover the most important ones in detail.