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Optimizing Time to Insight to Power Business Success

Michael Segal

Businesses everywhere continually strive for greater efficiency.

By way of illustration, more than a third of IT professionals cite "moving faster" as their top goal for 2018, and improving the efficiency of operations was one of the top three stated business objectives for organizations considering digital transformation initiatives.

As a result, Time To Insight, or TTI, which refers to the measure of the time it takes to collect, organize, and analyze the amount of information necessary to generate the intelligence an organization requires, has become intrinsic to business success.

81% of organizations say an hour of downtime costs them over $300,000

In today's competitive environment, where everything happens in real time, it's no longer viable to take hours — or even days — to analyze the volume and variety of data needed to provide a business with any meaningful insight. In addition, service downtime can have huge implications for businesses; 81% of organizations say an hour of downtime costs them over $300,000. Therefore, the shorter a company's TTI, the faster, more responsive, more efficient and more profitable they will be.

However, for businesses to gain the insight, they need to resolve issues or mitigate risks in the quickest possible time, they need to adjust their approach to data.

Real-Time Meaningful and Actionable Insights

It has been suggested that 90 percent of all the world's data has been created within the last two years. With such explosive growth and evolution of advanced analytics techniques that can convert this information into actionable intelligence, data is now widely considered to be as valuable as oil. As a result, businesses have been collecting and storing increasingly large volumes of information of data from a myriad of devices, systems and applications in the hope that it will become lucrative.

But, as the volume of data continues to grow, companies need to consider re-evaluating the way they handle data, and look toward a smart data approach. This involves harvesting all the important information from every action and transaction that traverses the entire enterprise infrastructure through traffic flows and compressing it into metadata at its source.

Importantly, a smart data approach represents greater efficiency. Once collected, smart data is normalized, organized, structured in a service-contextual fashion, and made available in real-time, all of which will significantly increase the efficiencies of analytics, improve the quality of the intelligence and reduce an organization's TTI.

Furthermore, smart data offers a high level of veracity. Constant monitoring of the wire data that traverses the infrastructure allows users to harvest all relevant key service assurance and threat indicators, which means that rather than simply having a select snapshot of sampled data, businesses are able to access contextualized data that provides real-time, continuous, and actionable insights across their entire IT infrastructure.

Cutting Costs

In addition, smart data's advantages can extend beyond just business efficiencies.

The traditional approach to service assurance, threat management, and business analytics involves collecting large amounts of data from multiple systems, applications and infrastructure components and sending it to a central location for storage and processing. This approach increases the required storage, processing and networking capacity and cost and has environmental implications, when you consider that server farms and networks account for 50 percent of the electricity consumption in our connected world.

With a smart data approach, the volume of the collected data is significantly compressed, since the raw traffic flows are processed at the source and metadata is created. It is therefore possible to keep only the data that is valuable for the task at hand, and discard the unnecessary overhead, thus both saving costs and reducing energy consumption.

What's more, as business everywhere undergo a form of digital transformation to enhance the speed and agility of their operations, smart data is able to significantly improve their Time To Insight, in strategic areas of service assurance and threat management. Through this approach, they are able to gain an additional edge in an increasingly competitive market. Considering the overwhelming benefits smart data can offer, it won't be long before it becomes the dominant approach to service assurance, threat management, operations management and business analytics.

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Optimizing Time to Insight to Power Business Success

Michael Segal

Businesses everywhere continually strive for greater efficiency.

By way of illustration, more than a third of IT professionals cite "moving faster" as their top goal for 2018, and improving the efficiency of operations was one of the top three stated business objectives for organizations considering digital transformation initiatives.

As a result, Time To Insight, or TTI, which refers to the measure of the time it takes to collect, organize, and analyze the amount of information necessary to generate the intelligence an organization requires, has become intrinsic to business success.

81% of organizations say an hour of downtime costs them over $300,000

In today's competitive environment, where everything happens in real time, it's no longer viable to take hours — or even days — to analyze the volume and variety of data needed to provide a business with any meaningful insight. In addition, service downtime can have huge implications for businesses; 81% of organizations say an hour of downtime costs them over $300,000. Therefore, the shorter a company's TTI, the faster, more responsive, more efficient and more profitable they will be.

However, for businesses to gain the insight, they need to resolve issues or mitigate risks in the quickest possible time, they need to adjust their approach to data.

Real-Time Meaningful and Actionable Insights

It has been suggested that 90 percent of all the world's data has been created within the last two years. With such explosive growth and evolution of advanced analytics techniques that can convert this information into actionable intelligence, data is now widely considered to be as valuable as oil. As a result, businesses have been collecting and storing increasingly large volumes of information of data from a myriad of devices, systems and applications in the hope that it will become lucrative.

But, as the volume of data continues to grow, companies need to consider re-evaluating the way they handle data, and look toward a smart data approach. This involves harvesting all the important information from every action and transaction that traverses the entire enterprise infrastructure through traffic flows and compressing it into metadata at its source.

Importantly, a smart data approach represents greater efficiency. Once collected, smart data is normalized, organized, structured in a service-contextual fashion, and made available in real-time, all of which will significantly increase the efficiencies of analytics, improve the quality of the intelligence and reduce an organization's TTI.

Furthermore, smart data offers a high level of veracity. Constant monitoring of the wire data that traverses the infrastructure allows users to harvest all relevant key service assurance and threat indicators, which means that rather than simply having a select snapshot of sampled data, businesses are able to access contextualized data that provides real-time, continuous, and actionable insights across their entire IT infrastructure.

Cutting Costs

In addition, smart data's advantages can extend beyond just business efficiencies.

The traditional approach to service assurance, threat management, and business analytics involves collecting large amounts of data from multiple systems, applications and infrastructure components and sending it to a central location for storage and processing. This approach increases the required storage, processing and networking capacity and cost and has environmental implications, when you consider that server farms and networks account for 50 percent of the electricity consumption in our connected world.

With a smart data approach, the volume of the collected data is significantly compressed, since the raw traffic flows are processed at the source and metadata is created. It is therefore possible to keep only the data that is valuable for the task at hand, and discard the unnecessary overhead, thus both saving costs and reducing energy consumption.

What's more, as business everywhere undergo a form of digital transformation to enhance the speed and agility of their operations, smart data is able to significantly improve their Time To Insight, in strategic areas of service assurance and threat management. Through this approach, they are able to gain an additional edge in an increasingly competitive market. Considering the overwhelming benefits smart data can offer, it won't be long before it becomes the dominant approach to service assurance, threat management, operations management and business analytics.

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Industry experts offer predictions on how AI will evolve and impact technology and business in 2025. Part 3 covers AI's impact on employees and their roles ...

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E-commerce is set to skyrocket with a 9% rise over the next few years ... To thrive in this competitive environment, retailers must identify digital resilience as their top priority. In a world where savvy shoppers expect 24/7 access to online deals and experiences, any unexpected downtime to digital services can lead to significant financial losses, damage to brand reputation, abandoned carts with designer shoes, and additional issues ...

Efficiency is a highly-desirable objective in business ... We're seeing this scenario play out in enterprises around the world as they continue to struggle with infrastructures and remote work models with an eye toward operational efficiencies. In contrast to that goal, a recent Broadcom survey of global IT and network professionals found widespread adoption of these strategies is making the network more complex and hampering observability, leading to uptime, performance and security issues. Let's look more closely at these challenges ...

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The 2025 Catchpoint SRE Report dives into the forces transforming the SRE landscape, exploring both the challenges and opportunities ahead. Let's break down the key findings and what they mean for SRE professionals and the businesses relying on them ...

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Gartner revealed its top strategic predictions for 2025 and beyond. Gartner's top predictions explore how generative AI (GenAI) is affecting areas where most would assume only humans can have lasting impact ...

The adoption of artificial intelligence (AI) is accelerating across the telecoms industry, with 88% of fixed broadband service providers now investigating or trialing AI automation to enhance their fixed broadband services, according to new research from Incognito Software Systems and Omdia ...

 

AWS is a cloud-based computing platform known for its reliability, scalability, and flexibility. However, as helpful as its comprehensive infrastructure is, disparate elements and numerous siloed components make it difficult for admins to visualize the cloud performance in detail. It requires meticulous monitoring techniques and deep visibility to understand cloud performance and analyze operational efficiency in detail to ensure seamless cloud operations ...