Skip to main content

5 Ways to Gain Operational Insights on Big Data Analytics

Michael Segal

We are starting to see an age where speed-of-thought analytical tools are helping to quickly analyze large volumes of data to uncover market trends, customer preferences, gain competitive insight and collect other useful business information. Likewise, utilizing ‘big data’ creates new opportunities to gain deep insight into operational efficiencies.

The realization by business executives that corporate data is an extremely valuable asset, and that effective analysis of big data may have a profound impact on their bottom line is the key driver in the adoption of this trend. According to IDC, the big data and analytics market will reach $125 billion worldwide in 2015, which will help enterprises across all industries gain new operational insights.

Effective integration of big data analytics within corporate business processes is critical to harness the wealth of knowledge that can be extracted from corporate data. While a variety of structured and unstructured big data is stored in large volumes on different servers within the organization, virtually all this data traverses the network at one time or another. Analysis of the traffic data traversing the network can provide deep operational insight, provided there is an end-to-end holistic visibility of this data.

To ensure holistic visibility, the first step is to select a performance management platform that offers the scalability and flexibility needed to analyze large volumes of data in real-time.

The solution should also include packet flow switches to enable passive and intelligent distribution of big data that traverses the network to the different location where the data is analyzed.

Here are five ways IT operations can use Big Data analytics to achieve operational efficiencies:

1. Holistic end-to-end visibility

A holistic view, from the data center and network to the users who consume business services, helps IT see the relationships and interdependencies across all service delivery components; including applications, network, servers, databases and enabling protocols in order to see which user communities and services are utilizing the network and how they’re performing.

2. Big Data analysis based on deep packet inspection

Deep packet analysis can be used to generate a metadata at an atomic level which provides comprehensive, real-time view of all service components, including physical and virtual networks, workloads, protocols, servers, databases, users and devices to help desktop, network, telecom and application teams see through the same lens.

3. Decreased downtime

A Forrester survey shows 91% of IT respondents cite problem identification as the number one improvement needed in their organization’s IT operations. As applications and business services’ complexity increases, reducing costly downtime will hinge on proactively detecting service degradations and rapid triage to identify its origin, which can be done through the right performance management platform.

4. Capacity planning

Accurate evidence is vital when it comes to making capacity planning decisions for your network and business processes. Benefits of metadata at an atomic level will aid in understanding the current and future needs of your organization’s services, applications and its community of users in order to identify how resources are being consumed.

5. Hyper scalability

Big data analytic tools that can scale to increasing data traffic flows provide key vantage points throughout your IT environment and offer rapid insight to meet the monitoring needs of high-density locations in data center and private/hybrid cloud deployments to help organizations achieve consistent service quality and operational excellence.

Network traffic Big Data analytics, made possible by today’s service performance management platforms, is changing the scope and quality of IT operational efficiencies. These platforms and technologies are not only protecting organizations against service degradations and downtime, but also serve to add new dimensions and context around interactive data making corporate data today an extremely valuable asset.

The Latest

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...

5 Ways to Gain Operational Insights on Big Data Analytics

Michael Segal

We are starting to see an age where speed-of-thought analytical tools are helping to quickly analyze large volumes of data to uncover market trends, customer preferences, gain competitive insight and collect other useful business information. Likewise, utilizing ‘big data’ creates new opportunities to gain deep insight into operational efficiencies.

The realization by business executives that corporate data is an extremely valuable asset, and that effective analysis of big data may have a profound impact on their bottom line is the key driver in the adoption of this trend. According to IDC, the big data and analytics market will reach $125 billion worldwide in 2015, which will help enterprises across all industries gain new operational insights.

Effective integration of big data analytics within corporate business processes is critical to harness the wealth of knowledge that can be extracted from corporate data. While a variety of structured and unstructured big data is stored in large volumes on different servers within the organization, virtually all this data traverses the network at one time or another. Analysis of the traffic data traversing the network can provide deep operational insight, provided there is an end-to-end holistic visibility of this data.

To ensure holistic visibility, the first step is to select a performance management platform that offers the scalability and flexibility needed to analyze large volumes of data in real-time.

The solution should also include packet flow switches to enable passive and intelligent distribution of big data that traverses the network to the different location where the data is analyzed.

Here are five ways IT operations can use Big Data analytics to achieve operational efficiencies:

1. Holistic end-to-end visibility

A holistic view, from the data center and network to the users who consume business services, helps IT see the relationships and interdependencies across all service delivery components; including applications, network, servers, databases and enabling protocols in order to see which user communities and services are utilizing the network and how they’re performing.

2. Big Data analysis based on deep packet inspection

Deep packet analysis can be used to generate a metadata at an atomic level which provides comprehensive, real-time view of all service components, including physical and virtual networks, workloads, protocols, servers, databases, users and devices to help desktop, network, telecom and application teams see through the same lens.

3. Decreased downtime

A Forrester survey shows 91% of IT respondents cite problem identification as the number one improvement needed in their organization’s IT operations. As applications and business services’ complexity increases, reducing costly downtime will hinge on proactively detecting service degradations and rapid triage to identify its origin, which can be done through the right performance management platform.

4. Capacity planning

Accurate evidence is vital when it comes to making capacity planning decisions for your network and business processes. Benefits of metadata at an atomic level will aid in understanding the current and future needs of your organization’s services, applications and its community of users in order to identify how resources are being consumed.

5. Hyper scalability

Big data analytic tools that can scale to increasing data traffic flows provide key vantage points throughout your IT environment and offer rapid insight to meet the monitoring needs of high-density locations in data center and private/hybrid cloud deployments to help organizations achieve consistent service quality and operational excellence.

Network traffic Big Data analytics, made possible by today’s service performance management platforms, is changing the scope and quality of IT operational efficiencies. These platforms and technologies are not only protecting organizations against service degradations and downtime, but also serve to add new dimensions and context around interactive data making corporate data today an extremely valuable asset.

The Latest

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Today, organizations are generating and processing more data than ever before. From training AI models to running complex analytics, massive datasets have become the backbone of innovation. However, as businesses embrace the cloud for its scalability and flexibility, a new challenge arises: managing the soaring costs of storing and processing this data ...