It seems that with every passing year, the applications for advanced analytics in business and society continue to grow. With millions of small and large companies vying for a competitive advantage in their respective markets, there’s a premium on the ability to collect and analyze real-time data to get insights.
Maximizing the data you collect requires having a robust business intelligence and analytics infrastructure that supports the collection, processing, and sharing of real-time data. Data fabric is a tool that eases data management and the sharing of data from various data sources and locations, making it easier for companies to respond to markets and collaborate on data-sensitive projects. Continue reading to learn some of the many use cases for data fabric.
Data fabric makes sharing data easier and safer.
Today, we live and operate in a global economy, and there are many companies that operate in different regions of the United States and even on various continents. Due to the shift toward a global economy, companies need the ability to share data assets quickly and safely.
Data fabric architectures promote data access by allowing anyone who’s a part of your company, regardless of location, to have access to timely data. TIBCO’s data scientists work to create new technologies that transcend data silos and make data discovery and sharing seamless for multi-national organizations, partnerships, and transactions.
Data fabric makes data integration more time and cost-efficient.
Traditional means of data integration and data management took too much time, effort, and capital to maximize the business value of analytics. Performing data discovery processes on legacy data sources such as data warehouses, databases, data lakes, and data stores was a time-intensive process. However, big data fabric employs machine learning technology to automate integration, data management, and data virtualization, joining data from various data sources onto a single platform.
Data fabric ensures the integrity of data assets from end to end.
When pulling diverse data from various sources of data, the accuracy of data becomes a challenge. Legacy file systems and other data tools aren’t capable of integrating different types of data from various data sources accurately. Data fabric ensures the reliability of data so business users in various locations using different data systems can get the same actionable insights in real-time.
Enterprise data fabric solutions make supply chain management easier.
One of the most common use cases of big data fabric is supply chain management. Companies use source data to find new suppliers and manage demand changes. Big data fabric provides context to source data, and data engineers create algorithms for machine learning computers that enable data discovery and processing without human intervention. Furthermore, big data fabric uses data integration tools to clean different data types, allowing companies to create supply chain plans for various scenarios based on the right data at the right time.
Data fabric solutions provide agility and scalability.
As technology and customer demands evolve, enterprise data infrastructures need to have the agility and scalability to grow and evolve with the needs of business users. Legacy systems have to undergo complete overhauls to meet the requirements of advancements in data tools and processes.
As you can imagine, traditional means of scaling enterprise data infrastructures are costly and time-consuming. Data fabric creates a portal that allows for the transformation of data discovery and analytics processes with time.
In this global economy, small businesses and large enterprises need to be able to share and manage uncompromised data to enhance the customer experience, optimize supply chains, and maximize production. Big data fabric platforms allow the sharing and management of real-time data using machine learning, the internet of things, and advanced analytics to provide security and data quality across cloud environments.
