Data management agility has become a mission-critical priority for organizations in an increasingly diverse, distributed, and complex environment. "The emerging design concept called "data fabric" can be a robust solution to ever-present data management challenges, such as the high-cost and low-value data integration cycles, frequent maintenance of earlier integrations, the rising demand for real-time and event-driven data sharing and more," says Mark Beyer, Distinguished VP Analyst at Gartner. Gartner defines data fabric as a design concept that serves as an integrated layer (fabric) of data and connecting processes. A data fabric utilizes continuous analytics over existing, discoverable and inferenced metadata assets to support the design, deployment and utilization of integrated and reusable data across all environments, including hybrid and multi-cloud platforms. Data fabric leverages both human and machine capabilities to access data in place or support its consolidation where appropriate. It continuously identifies and connects data from disparate applications to discover unique, business-relevant relationships between the available data points.
Integrating big data is hard. Without a single automated way of unifying, accessing and controlling different multi-formatted data sources, organizations can end up with a lot of "Big Data" silos, but no real business value. What is needed is a way to organize data from disparate sources so the right data gets to the right application at the right time. One solution that has recently come to the fore is the data fabric. This emerging platform automates big data integration by creating a single access layer to all data sources, from traditional analytic databases and enterprise data warehouses (EDWs) to repositories like Hadoop, Spark, and NoSQL databases.
There are certain things that humans -- or enough loud people, anyway -- respect as universal truths. Wearing socks to bed is terrible and should be a crime. The first two are absolutely inarguable, but, friends ... sometimes wearing socks to bed is nice. If you suffer from dry skin or are constantly cold, it can be even nicer. Here's how to make it replace your personality First, sock haters, I ask you to think of your sleep cycle.
Data fabric is expected to be a key focus area for organisations this year, as they look to optimise the value of their data. This is a logical progression, as organisations spread across regional boundaries and increasingly need to integrate external data into their planning and forecasting, and seek to automate ingestion, integration and exploration, embed governance, and enable self-service across the enterprise. Data fabrics add a semantic layer to data lakes, making the vast volumes of data spread across a complex ecosystem of devices, applications and data infrastructure more readily available for consumption and reducing time to delivery. Unlike data mesh, which connects data on the fly and plugs in various functionalities, a data fabric is architecturally in place – with data interlinked, partitioned and served up off a platform. Data warehouses and data lakes are becoming limited in terms of functionality – they have become too large and may not have all the data the organisation needs, including data from external sources such as weather patterns or social media behaviour.
The clothes on your back don't just make you look good. They keep you warm and dry, make movement easier and make your life better. Fabric technology has a huge impact your day-to-day. From early advances with chemistry that gave us synthetic fabrics to treatments that are revolutionizing the idea of what clothing can do, textile tech is expanding to new and exciting places. Here we'll explore the technology behind these advances, take a look at how far we've come and peek ahead to see where we're going.