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.
All the information that traverses the IT service delivery infrastructure – the “wire data” – can be utilized to generate smart data, but it must be properly processed to distill the most meaningful intelligence. Once the intelligence has been extracted from the wire data, it can be compressed into a much smaller and meaningful metadata and then stored for back in time and forensic analysis. Unlike storing large volumes of log data, which is exceptionally inefficient and forces businesses to pay for excessive storage costs, the smart data approach means that enterprises are only paying to store data that holds real value for them. As a result, it is much more cost-efficient, and enables enterprises to quickly and easily get access to the data that matters.
Timing is everything
To unlock smart data’s true value, timing is essential. In this highly competitive age, companies have become so dependent on the speed and scale of IT systems forming the backbone of their business that every adjustment, upgrade and data packet needs to be monitored closely to ensure smooth operation. Now enterprise IT infrastructure has become so vast and complex through the introduction of IoT, broadband wireless and wireline technologies, cloud services and applications, there is greater room for disruption and service failures – not only to the network itself, but also the ability for enterprises to access and take action upon the valuable data insights.
It is therefore imperative that companies continuously monitor the entire infrastructure environment in real-time – including network, compute, and storage systems – to find and isolate problems before the end user is impacted. Ultimately, businesses that do not have a handle on what is happening every second and every minute of every day will not be able to survive in this new digital economy. Instead, they need to catch problems as they arise, resolving them before they become a widespread issue.
While many service assurance solutions profess to offer so-called ‘real time,’ in many cases, it takes time to collect logged events, normalize, and organize them before the data can be analyzed. This means that even if the analysis of the log data is prompt, the collection and organization of this information is not. As a result, businesses risk disruptions and service failures going undetected for a considerable time, which could cause huge damage, particularly in cases of a security breach. It is therefore important that for service assurance purposes, traffic flow and wire data are converted into smart data immediately, at the source. Only through this approach will be companies be able to gain access to actionable intelligence from the start, and stop any issues in their tracks.
In today’s digital age, data has become the lifeblood of any business. It enables companies to gain insight into service performance and security issues to tackle problems immediately, understand more about customers’ habits to create the best possible experience, increase efficiency and create new data-driven business models. However, with data often unstructured and from a disparate set of resources, sourcing actionable intelligence depends on having the right tools in place to begin with. Enterprises must therefore utilize service assurance technology to unlock the smart data that’s contained in the wire data. Through this approach, they will be able to drive internal and external business success, and continue their smart data guided journey through the chaotic seas of digital transformation.
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