The amount of data being created today is expected to increase ten-fold in less than a decade, it’s also anticipated that enterprises will produce around 60% of global data by 2025. However, while the amount of data may be growing exponentially, the intelligence gleaned from it is not.
Instead, companies can be subject to a barrage of unstructured data delivered at high velocity from a variety of different sources with limited ability to convert it into actionable insight. As a result, enterprises risk useful information getting lost amidst the sheer volume of noise.
This is set to be further compounded by the widespread adoption of IoT technologies in both consumer and enterprise markets. The proliferation of IoT sensors, mobile devices and digital services, combined with advent in big data technologies and broadband networks increase the volume, velocity and variety of data traversing the connected world. This means that businesses that collect relevant data that flows through their corporate networks and the connected world are sitting on an abundance of data, which will only increase.
Mission contextual analysis of this data can provide invaluable insight to corporations in a variety of areas and improve business outcomes. For example, gleaning insight into digital services performance, and customer experience, usage, and behavior, which in turn can be harnessed to drive efficiencies and revenue, improve the customer experience or digitally transform the business.
But simply having access to big data is not enough. It is vital that enterprises have the right tools to convert this information into business insight, and ensure it is properly utilized to support both operations and the bottom line.
Harnessing smart data
Businesses that rely on a dataset that has not been normalized, organized, correlated and analyzed in the context of the relevant business intelligence, are not effective. For example, businesses that rely on effective delivery of digital services and outstanding user experience must leverage smart data to gain actionable insight in these areas. This insight can then be used for service assurance purposes to ensure high service performance and delightful user experience.
So, what exactly is smart data in the context of service assurance? Smart data is the inherent intelligence of the metadata to enable analytics tools to clearly understand application performance, infrastructure complexities, and service dependencies. It is normalized, organized, structured, service contextual, and available in real-time. It is generated based on end-to-end pervasive visibility across physical, virtual and cloud environments.
Pervasive visibility has two key dimensions: depth of visibility and breadth of visibility. Meaning organizations have complete visibility of all transactions taking place across their entire IT infrastructure, as well as the understanding of how end-users are consuming all of the services that this infrastructure enables.
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