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Better Risk Management With Big Data Analytics And Capacity Optimization


By: Ahmed Banafa


Big data analytics and capacity optimization are important techniques used by organizations for improving risk management and saving resources by optimizing the performance of different departments, including IT. To understand the impact of such techniques, you need to know what they entail: big data analytics is an advanced process to explore, analyze, and examine an organization's data (structured and unstructured) for the purpose of finding hidden patterns, correlations, and other important dimensions. This type of information can be used to make decisions that will improve business processes inside and outside the organization, including IT performance, risk management, and customer experience and behavior, to name a few. Capacity optimization is a technique used to save valuable storage space by analyzing stored data and identifying repetitive patterns to avoid duplicated data, which is especially important with today's huge data volumes.


Big data analytics Why optimize IT performance?

Using both techniques to optimize IT performance and improve risk management is one of the new trends changing the traditional concept of auditing and analyzing IT tasks. The use of these techniques expands IT performance in two ways: by reducing the costs of delivering IT services and leveraging current IT assets to achieve organizational goals. Both of these help organizations reduce costs, avoid risks, and open themselves up to new business opportunities.


Before optimizing the performance of any IT organization, however, you need to analyze and assess all components of the IT infrastructure, including anything with an IP address (servers, desktops, routers, and so on) as well as utilization and virtualization, to determine which components to keep and which to consolidate or remove. Also, you must gather information about software performance to determine which solutions need to be updated, renewed, or patched.


IT and big data analytics

One of the main goals of IT optimization is to identify and remove overlapping IT resources to achieve better performance, better risk management, improved security, and reduction in costs. Big data analytics can provide all this information in real time.


One major aspect of improving IT performance is improved security. Big data analytics is key for IT security when dealing with security breaches, such as cyberattacks. Big data analytics can analyze massive volumes of real-time data, including log files, vulnerability scan reports, alerts, and more. IT managers will gain a comprehensive view of their security landscapes, exposing what components are at risk and the level of risk involved. This technique can be expanded and used to track and protect IT assets, regardless of their location. Big data analytics can also be used to address more nebulous threats and to generate profiles to anticipate future attacks.


IT and capacity optimization

The second technique used to improve IT performance is capacity optimization, which can be achieved by combining storage optimization, software integration, and selective hardware upgrades. With today's enormous volume, velocity, and variety of data being processed by organizations' IT infrastructures, the need for capacity optimization is becoming more urgent.


The magic of capacity optimization resides in the balancing of capacity needs and high performance and handling of traffic. The increased data growth creates bottlenecks and blocks in networks, leading to a deteriorating quality of experience and service for everyone inside and outside the organization. The benefits of using capacity optimization will expand beyond the IT department to the other business activities, bringing OPEX reduction, CAPEX optimization, quality improvements, and revenue increases, with a reduction in customer churn.


As organizations migrate toward the new era of IT infrastructure and operations, the use of new tools and techniques such as big data analytics and capacity optimization will be one way to support the dynamic and complex nature of today's business activities. With this in mind, IT teams are now able to detect real-time warnings of incidents as they happen, as well as use advanced techniques to help diagnose specific areas to understand long-term trends and relationships that will help increase service availability, velocity, and efficiency.


IT leaders are embracing change with widespread adoption of Big Data and analytics technology. Are you? Count the ways to make your data more valuable [infographic].



About the author

Banafa AhmedAhmed Banafa


Extensive experience in IT operations and management, as well as a research background in a variety of techniques and analysis of new technology trends. Ahmed is a professor, reviewer, and technical contributor.

About the author

Connect with Ahmed:

 Follow me on Twitter @banafaahmed

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