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What is Metadata Management? Benefits, Framework, Tools, Use Cases, Best Practices

Before shedding light on metadata management, it is crucial to understand what metadata is. Metadata refers to the information about your data. This data includes elements representing its context, content, and characteristics. It helps you discover, access, use, store, and retrieve your data, having a wide spread of variations. Metadata of an image. Image by Astera. Let’s look at some of the metadata types below.

Targeting Robot at a Specific Window: A Deep Dive into Katalon Studio

Hello, Katalon users and software testing enthusiasts! Today, we’re going to delve into a topic that has been buzzing in our community forum: How to target a robot at a specific window in Katalon Studio. This blog post is aimed at experienced software testing professionals who are familiar with Katalon, or those looking to switch to the Katalon Platform.

Exploring the Future of User Experience in Banking and Fintech

It’s Monday morning, and Sam woke up to a gentle sound on his phone. It’s not an alarm but his new financial pal—a voice-activated AI assistant. This friendly voice, tailored to his financial goals, provides a personalized morning briefing of his accounts, highlights upcoming bills, and even suggests budget-friendly options for his breakfast. After a busy workday, Sam stared at his evening coffee.

Insight With Eyesight: Qlik Introduces a New Era of Visualization

Our ability to tell stories is an art form as old as language itself. From ancient cave paintings to oral traditions passed through generations, the essence of stories has evolved alongside our communication methods. It began with visual tales etched on cave walls, transitioned into spoken narratives, and eventually found its way into written, printed, and typed forms.

What Separates Hybrid Cloud and 'True' Hybrid Cloud?

Hybrid cloud plays a central role in many of today’s emerging innovations—most notably artificial intelligence (AI) and other emerging technologies that create new business value and improve operational efficiencies. But getting there requires data, and a lot of it. More than that, though, harnessing the potential of these technologies requires quality data—without it, the output from an AI implementation can end up inefficient or wholly inaccurate.

A Software Engineer's Tips and Tricks #4: Collaborating on Visual Studio Code with Live Share

Hey there! We're back for our third edition of Tips and Tricks, our new mini series where we share some helpful insights and cool tech that we've stumbled upon while working on technical stuff. Catch up on the previous posts: All of our posts are super short reads, just a couple of minutes tops. If you don’t like one of the posts, no problem! Just skip it and check out the next one. If you enjoy any of the topics, I encourage you to check out the "further reading" links.

All You Need to Know About Data Aggregation

Data aggregation is the process of combining and summarizing data from disparate sources into a cohesive dataset. It prepares data for analysis, making it easier to obtain insights into patterns and insights that aren’t observable in isolated data points. Once aggregated, data is generally stored in a data warehouse. Then, you can leverage it to gain a holistic perspective on your operations and market trends, design effective risk management practices, and make more informed decisions overall.