The PHP ErrorException class is meant to be thrown explicitly to catch and handle errors that would otherwise be ignored, such as Notices or Warnings.

In part one of this series, we successfully built a TypeScript Lambda on the AWS cloud. But we left a lot of room for improvement in terms of the developer experience. For starters, the Lambda didn’t run on a local machine, which is cumbersome. The code we wrote is also not testable, which makes refactoring hard or, at least, dangerous. In this take, let’s focus on improving the developer experience. The goal is to make the code more robust and easier to work with. Ready?

The key to Extract-Load then Transform (ELT) is that the data is landed in a normalized schema. Why? Correctness, flexibility and understandability.

You have been putting in the work, and your company has been growing manifold, Your client base is growing more than ever, and the projects are pouring in. So what comes next? it is now time to focus on the data that you are generating. When programming an application, DevOps engineers keep track of many things, such as bugs, fixes, and the overall application performance. This ensures that the application operates with minimum downtime and that any future errors can be predicted.

It’s no secret that advancements like AI and machine learning (ML) can have a major impact on business operations. In Cloudera’s recent report Limitless: The Positive Power of AI, we found that 87% of business decision makers are achieving success through existing ML programs. Among the top benefits of ML, 59% of decision makers cite time savings, 54% cite cost savings, and 42% believe ML enables employees to focus on innovation as opposed to manual tasks.

When you look closer at the Modern Data Stack (MDS) you need to brace yourself. The number of tools companies use for their databases, user administration, data extraction, data integration, security, machine learning, and a myriad of other use cases has grown astronomically. Matt Turck, VC at FirstMark, composes a yearly infographic of the hot tools in the datascape: And this is just a shortlist of both the most popular and fastest-growing tools.

Billions of people rely on WhatsApp each day to communicate in realtime. Friends exchange memes, expats catch up with their families, businesses take bookings and run customer support, and teams ranging from emergency services to on-call engineers at tech companies even use WhatsApp as their primary communication tool. So when WhatsApp had an hours-long global outage on 25 October 2022, the world noticed.

In this post, we will implement a basic ActionText table editor for your Rails application. We'll learn how: This article draws inspiration from the excellent 'Adding Tables to ActionText With Stimulus.js' blog post from 2020. That was written before the advent of Turbo though, which we can expect to simplify matters quite a bit. Let's get going!

SQL is the universal language of data modeling. While it is not what everyone uses, it is what most analytics engineers use. SQL is found all across the most popular modern data stack tools; ThoughtSpot’s SearchIQ query engine translates natural language query into complex SQL commands on the fly, dbt built the entire premise of their tool around SQL and Jinja. And within your Snowflake data platform, it’s used to query all your tables.