Systems | Development | Analytics | API | Testing

Google Cloud customers who want app-level encryption in hybrid cloud data warehouses can encrypt and decrypt that data outside BigQuery. Here’s how to do that securely.

Do you need complete control over your production environment? If so, you might want to skip the Platform as a Service (PaaS) offerings and deploy to your own server instead. This article describes deploying a Django application to an Ubuntu server at Linode.

The Chief Data Officer is arguably one of the most important roles at a company, particularly those that aspire to be data-driven. CDO appointments and the elevation of data leaders have accelerated in recent years, and the role has morphed as perceptions of data have evolved. Responsibilities span strategy and execution, people and processes, and the technology needed to deliver on the promise of data.

Artificial Intelligence (AI) is coming, whether we like it or not. It is likely to transform every aspect of what it means to be human and represents an existential opportunity – or potential threat – to everyone living and yet to be born. Hyperbole aside, ChatGPT software intelligence has been a hot news topic of late. While it has some limitations, to many of us it’s the first real glimpse of AI’s capabilities.

The urllib.error.HTTPError is a class in the Python urllib library that represents an HTTP error. An HTTPError is raised when an HTTP request returns a status code that represents an error, such as 4xx (client error) or 5xx (server error).

Recently, I published a blog on whether self-service BI is attainable, and spoiler alert: it certainly is. Of course, anything of value usually does require a bit of planning, collaboration, and effort. After the article was published, I began having conversations with technical leaders, analysts, and analytics engineers, and the topic of data modeling for self-service analytics came up repeatedly.

Extract, transform, load (ETL) is a critical component of data warehousing, as it enables efficient data transfer between systems. In the current scenario, Python is considered the most popular language for ETL. There are numerous Python-based ETL tools available in the market, which can be used to define data warehouse workflows. However, choosing the right ETL tool or your needs can be a daunting task.