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By now, most healthcare leaders know that their sector is a top target for ransomware.

With skyrocketing inflation and growing severity of weather-related losses, 2022 was a tough year for insurers. We were spot-on with our 2022 predictions—such as the need to improve the customer experience, increased adoption of connected underwriting, and the growing importance of ESG. While many of last year’s trends will continue into 2023, we have identified several emerging trends for this year.

With operations in 70 countries, Allianz is a world leading insurance company and the preferred insurance brand. The company offers a large range of insurance policies for both corporates and individuals. Allianz has been present in France since the late 1950s and made a major acquisition there in 1998 with the purchase of the AGF company. 5 years ago, Allianz France decided to reorganize its IT to scale agile practices.

Do you find yourself frustrated with loops that never seem to end? Do you find yourself wishing you could skip certain iterations or exit a loop prematurely? Python's break and continue statements are here to save you! One of the key features of Python is its ability to control the flow of code using control flow statements. Two of the most commonly used control flow statements in Python are break and continue.

A data lakehouse is a data storage repository designed to store both structured data and data from unstructured sources. It allows users to access data stored in different forms, such as text files, CSV or JSON files. Data stored in a data lakehouse can be used for analysis and reporting purposes.

When it comes to WebRTC testing, there aren’t many feature-rich tools on the market. Loadero is one of those, testRTC is another widely known option, so we get questions about how those two compare frequently. To give a detailed answer to that question, we published this blog post in which we attempted to make a comprehensive comparison of the two tools.

Abstraction is one of the key concepts of object-oriented programming (OOP) languages. Its main goal is to handle complexity by hiding unnecessary details from the user. That enables the user to implement more complex logic on top of the provided abstraction without understanding or even thinking about all the hidden complexity. That’s a very generic concept that’s not limited to object-oriented programming. You can find it everywhere in the real world.

If you’ve ever worked with a database, you’ve likely worked with CRUD operations. CRUD operations are often used with SQL, a topic we’ve covered in depth (see this article, this one, and this one for some of our recent SQL tips and tricks). Since SQL is pretty prominent in the development community, it’s crucial for developers to understand how CRUD operations work. So, this article is meant to bring you up to speed (if you’re not already) on CRUD operations.

If you ever had to analyze an issue in production, I’m sure you know how important it is to have good logging. Good logging requires three things: While you still need to decide yourself which log messages you should write for each use case, you don’t need to worry about requirement 2 and 3. Various logging frameworks already solved these technical requirements. You only need to choose one of them and use it to write your log messages.

Who doesn’t love Apache Airflow? The Python-based open-source tool allows us to schedule and automate workflows with DAGs (Directed Acyclic Graphs). Data teams use Airflow for a myriad of use cases: from building ETL data pipelines to launching machine learning apps. The open-source tool makes workflow management easy: it is extensible, easy to monitor from the intuitive user interface in real time, and it allows you to build dependencies between jobs.