Discover how mobile teams building finance apps rate themselves across the five key Mobile DevOps metrics.

This guide will take you through the steps to build and host an API using Linx. It will cover building a straightforward API to retrieve product data. You will be provided with the data, instructions for what tools to use, relevant scripts and all steps to get the API live. It will take about 20 to 30 minutes to complete all steps.

Artificial Intelligence (AI) is quite powerful and is constantly evolving and currently knows no bounds. It is focused on outperforming its limits using the power of Machine Learning (ML). AI is empowering computers to do things that human beings are unable to do efficiently and effectively and machine learning is aiding the computers to do so by breaking the rules of traditional programming.

Many businesses are shifting their focus toward mobile app development as the demand for mobile apps increases. Innovative mobile apps are being developed with the help of new technologies, platforms, and frameworks. A new trend in mobile development is cross-platform app development, which allows developers to create apps for multiple platforms, such as Android, iOS, and Windows. By choosing React Native for your multi-platform mobile app development, you can be confident you made the right choice.

GitHub Copilot has been the subject of some controversy since Microsoft announced it in the Summer of 2021. Whatever your feelings about the matter, Copilot is likely here to stay. So that got me thinking — perhaps there are more important questions to ask about Copilot. If developers are going to use an AI-assisted code generation tool, it would be more productive to think about how to improve it rather than contemplating its right to exist.

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD).

So much relies on data these days that it might be safe to say that most companies can’t thrive without it. Yet, gathering data is just the start — using it to make better company decisions or improve business processes is the end goal. Unfortunately, collecting large quantities of data for your business might seem futile if that data remains cut off from other systems. As such, it has become vital for developers and decision-makers to unify data for practical use.

What does this mean for those of us managing or trying to understand fast-growing companies?

This is a guest post with exclusive content by Bill Inmon, Mary Levins, and Georgia Burleson. Bill “is an American computer scientist recognized by many as the father of the data warehouse. Inmon wrote the first book, held the first conference, wrote the first column in a magazine, and was the first to offer classes in data warehousing.” -Wikipedia.

The data landscape is exploding with tools. As data professionals we have at our fingertips specialized tools for anything: from specialized databases (graph, geo, you name it) to tools for SQL-driven transformations (looking at you, dbt). Yet, a lot of data work is about provisioning, selecting, administering, and just maintaining those tools. Which is just a pain. As Pavel Dolezal, CEO and co-founder of Keboola said: The answer is in how the Modern Data Architecture is built.