With the never-ending potential of technology to disrupt everyday processes, more and more industries are deciding to adapt to one exciting area of innovation today: artificial intelligence (AI). In fact, Global Industry Analysts Inc. predicts that AI will be worth 164.03 billion GBP by 2026, and here, we look at four industries set to be disrupted by AI. Since the healthcare sector collects and greatly depends on personal data from their patients, AI will play a crucial role in data management.

Sometimes, the data you want to analyze lives in AWS S3 buckets by default. If that’s the case for the data you need to work with, good on you: You can easily ingest it into an analytics tool that integrates with S3. But what if you have a data source — such as logs generated by applications running in a Kubernetes cluster — that isn’t stored natively in S3? Can you manage and analyze that data in a cost-efficient, scalable way? The answer is yes, you can.

For all of the buzz surrounding both artificial intelligence and data-driven management, many companies have seen mixed results in their quest to harness the value of enterprise data. To avoid those pitfalls, we mixed best-of-breed and proprietary solutions to develop our enterprise data platform (EDP), focusing much of our attention on a combination of smart changes in technology, culture and process for data lakes.

Like most organizations, Yellowfin has a CRM tool. The data in your CRM should be able to help you understand how you’re selling and how you win. But everyone I speak to is frustrated by the analytics they get from their CRM. We realized very quickly that the reporting in our CRM tool wasn't meeting our needs, so we built our own solution.

Despite Selenium's popularity across the QA industry, it has drawbacks and won’t be the best fit for everyone. Specifically, Selenium IDE: In this post, we'll compare seven alternatives to Selenium, focusing primarily on our platform, Rainforest QA, and explore how the alternatives approach solving these drawbacks.

APIs have long been the programmers tool of choice for inter-application communication. Built by programmers, for programmers. Giving each other an interface and a means by which to call each other’s code. As for documentation and ease of use, well….

At Koyeb, our mission is to provide the fastest way to deploy applications globally. We are building a platform allowing developers and businesses to easily run applications, a platform where you don't need to think and deal with the resiliency and scalability of your servers: a serverless platform. Ironically, a serverless platform is actually full of servers. As a cloud service provider, we operate the infrastructure for you and abstract it as much as possible.

A service mesh is a software infrastructure layer for controlling communication between services and usually tasked with handling all the network logic required to make microservice applications work seamlessly in a cloud-native environment. It’s the perfect solution to your communications problems.

As you develop your software, you want it to work well, not only on paper but also as the actual users interact with the application. The way to create quality software that is easy to use and bug-free is with end-to-end testing.

For data analysts, business intelligence professionals, and CTOs to optimize and scale business operations, they must first understand the business data that is available to them. One of the best platforms to turn complicated data points from multiple platforms into a singular, coherent data set is Microsoft Power BI. However, you must first prepare the data sets to eliminate fragmentations and create structural consistency. This article explores how to prepare data for Microsoft Power BI.