Market Overview:
Data fabric enables data management, data placement, performance optimization, and access management to allow storage resources to be automatically provisioned to the requesting users or applications in a self-service manner. Thus, data can move between storage systems within a data center and/or to the cloud without changing user processes.
The goal of the data fabric is to eliminate the storage sprawl that organizations are inflicting on themselves in an attempt to address data sprawl. Data sprawl is the result of the increasing number of cases for IT, ranging from multiple types of databases to unstructured data types as well as the core demands for virtualization.
The global Data Fabric Market is segmented on basis of type, application, services, vertical, and region. The vertical segment is further classified into BFSI, healthcare, automotive, energy and utilities, and media and entertainment. The energy and utilities industry is undergoing a major transformation with the advent of smart sensors, smart meters, and IoT-based technologies. This transformation is mainly driven by the opportunity to use the massive amount of data generated from oil wells, generation stations, utility grids, gas grids, and other sensors in distributed generations to derive meaningful insights for operational decision making. This data can provide unprecedented insights into asset utilization, real-time demand and supply gaps, and consumption behavior patterns – parameters key for business growth. Data gathered from smart devices across the network can provide better understanding of customer segmentation, behavior and the influence of pricing on usage.
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Some of the key players in the market are SAP SE (Germany), Informatica (U.S.), Splunk Inc. (U.S.), Denodo (U.S.), Syncsort Inc. (U.S.), IBM Corporation (U.S.), Oracle Corporation (U.S.), Global DS (U.S.), Teradata Corporation (U.S.), K2 View (U.S.), among others.
Some of the key imperatives driving energy and utilities companies to transform into a data-driven enterprise:
- Optimize expensive assets: The ability to identify potential problems in wells, power generation, grids, and power distribution equipment can extend the life of expensive assets and help to avoid unplanned service interruptions
- Dynamic forecasting and load management: Accurate and real-time energy demand forecasting is critical for timely and economical demand and supply management. Utilities need to leverage data on consumption, weather, and supply constraints to effectively manage their wholesale operations and minimize the need for expensive spot market power purchases
- Fraud and loss prevention
- Customer service level management
Many industry players like IBM, Splunk, and HP designed data fabric techniques for energy management organizations. With Splunk software, user can harness machine data to determine everything from operational health to the security posture of your infrastructure. It helps in monitoring the health of assets and systems in real time, protect critical infrastructure from cyber security threats, Gain real-time insights from sensors, devices, and industrial systems like SCADA.
Intel Corporation is providing smart grid data management, which improves utility system operation. It reduces the cost and complexity of Phasor Measurement Unit (PMU) technology while increasing scalability and lowering risk.
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Regional Analysis
The global data fabric market is being led by North America followed by Europe and Asia Pacific. The technological advancements and early adoption of data management systems in North America is likely to lead the market. The market in Asia Pacific is expected to grow rapidly over the forecast period. Increasing technological adoption and huge opportunities across industry verticals in APAC countries, especially India, China, and Japan are the major driver of the market.
Intended Audience
- Software Developers
- Testing
- Government
- End-Users
- Cloud service providers
- System integrators
- Advisory firms
- Technology providers
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