Discover the power of Low-Code Data Fabric in revolutionizing data management, enhancing productivity, and driving cost savings. Learn how this innovative approach combines low-code development and data fabric architecture to enable seamless integration, collaboration, and data-driven decision-making. Explore the benefits, challenges, and best practices of implementing Low-Code Data Fabric for your organization's digital transformation.

Low-code Data Fabric Architecture streamlines data management by consolidating and integrating data from multiple sources into a central location, providing businesses with accurate, consistent, and accessible data. Learn how this innovative solution can transform your data management game.

Data mesh is a term used by enterprises to refer to the process of linking disparate data sources. This can be achieved in many ways, but one of the most popular architectures for doing so is called data mesh architecture. In this article, we'll take an in-depth look at how this architecture works and the benefits it provides.

Data engineering is a growing field that brings together the physical world with the digital one. The problem is that data engineers are in short supply, and there aren't enough of them to go around. This article explores the issue of data engineers, whether they're necessary, what's causing the shortage, and if there are some other solutions to this problem.

Data management is a growing issue and one that is compounded every day. With the data being collected faster than ever before, manual methods of managing data are becoming less of an option. One way to combat this problem is through the use of modern AI tools which can automatically extract relevant information from large amounts of data.

Nowadays, more and more companies are embracing the idea of scalability, some even choose to deploy a system that scales automatically. However, there are three major types of scalability, and this article will briefly explain each one.

It’s no secret that data is a valuable asset for organizations. Businesses today are collecting more data than ever before, thanks to advancements in technologies like cloud computing, social media, and mobile devices. The growth of big data creates an opportunity not just to collect it, but also to use it to drive organizational decision-making by developing three core capabilities: data proficiency, analytics agility, and community.

We’re inundated with new opportunities, more requirements, and more information than ever before. It can be overwhelming to try to keep up with the latest research, the newest software, and the hottest new thing.

The global technology landscape is increasingly accelerating towards more disruption, this time at an unprecedented scale. We are moving beyond rapid digitization, to hyper-connectivity, data analytics, and intelligent automation solutions that reach well beyond the boundaries of enterprises.

Data is key to any business. And while there is no silver bullet for making data work for your business, it does hold several keys. In this post, we’ll explore the use of data to inform your everyday activity and how it can help you to make better decisions in an ever-evolving industry.

Today’s business executives must master the fine art of driving down costs and increasing operational efficiency. A key lever for improving both of those metrics is data.

A number of organizations are harnessing the power of predictive analytics to drive measurable ROI. Consider some examples: a large retailer with a major national brand that needed to reduce its customer churn rate (the percentage of customers who stop doing business with the firm).

Big data is an enabler. In the wake of the crisis, we have learned a lot about big data in action during the COVID-19 crisis. These lessons will make it easier for governments, enterprises, and vendors to deliver better big data projects and products. Visualization is paramount. With detection time measured in minutes instead of days, forecasters are forced to visualize every bit of data available.

Big data is a term that was coined by William H. Inmon in 1996. The purpose of using this term was to explain the management problems in processing large amounts of data. The term big data has been coined to describe the massive amounts of data created all around the world every day.