The results of IT system operations are just the tip of the iceberg. Each component of the IT infrastructure – servers, networks, websites, applications, mobile devices, etc., executes enormous amounts of activities to support everyday operations. Machine data is a log of such activities. The data is in the form of log files, scripts, call records, user profiles and so on. It includes capturing structured and unstructured machine data. This raw log data serves as the basis of actionable insights that enables organizations to predict, identify, and solve problems such as performance issues and security leaks.

Organizations collect voluminous data of the activities taking place in all or selective components of their IT infrastructure. The goal behind this data gathering is to convert the data of background operations into useful performance insights. It is possible to optimize business operations and enhance profitability by monitoring and analyzing machine log data that is generated every second. So, log management solution can be offered across all the devices, applications, servers and the machine data to discover actionable insights on security and other related aspects.

Why Machine Data Is Important?

Each system, application, and device works similar to a cogwheel in your IT infrastructure. Therefore, it is crucial to monitor your entire IT infrastructure. Machine log data helps you to keep a close watch on their performance. Such vigilance into IT operations has a direct impact on reducing cost of ownership across your business.

There are several tools available that keeps system administrators from drowning in the massive machine data. These tools enable collecting such machine data in a way that it is accessible, searchable, and usable to derive operational insights. Eventually, the operational efficiency of an organization rests on its systems. Applications with security leaks or servers plagued with frequent issues can run havoc on the overall operational performance of the organization, which weighs heavily on profitability.

Data churning can be a cumbersome task but when done right, it can offer rewarding results. Machine log data has attracted attention from system administrators and IT heads because of the operational insights it enables, which results in improving business operations. For many organizations, the impact of machine data analysis helps in delivering a smooth and secured customer experience.

How Insights from Machine Data Can Effectively Charge Your Operational Efficiency

1. Keep a check on business-critical applications

System administrators are overwhelmed. Churning a large volume of data to make sense of it isn’t an easy job. Using advanced tools, organizations can conduct holistic and accurate diagnosis on machine data. This way the analysis can reveal insights into app issues relating to performance, user experience and more. It allows the organization to go beyond traditional methods of assessing application performance.

In case of an enterprise application, any shortcoming in app performance has far-reaching repercussions. Machine log data allows gaining insights into failure occurrences, and getting early warnings of failures of applications that power your business operations. Monitoring log data helps in managing downtime optimally so that overall efficiency of application users is affected the least.

Such information can be of even more critical use for customer facing applications. As soon as the system administrators identify a possibility of an outrage in the system, they can take preventive actions before the outrage causes inconvenience to customers or other stakeholders involved.

2. Enable operational visibility and intelligence

Machine log data offers scope for predictive intelligence as well. System administrators can analyze data collected overtime to derive pattern recognition and to form advanced correlation between selective activities. The result of this analysis can be of significant importance to resolve complex and undetectable events. It allows system administrators to notice problems early and accurately.

Historic machine data can serve as a sounding board to make future business decisions. When planning for expanding operations and adding new components to the IT infrastructure, the current capacity and performance can be identified from the historic machine data.

Moreover, predictive analysis of machine data has the potential to detect capacity issues in advance and prevent substantial business losses. It enables organizations to assess the optimal level of IT resources they require to meet the capacity requirements. As a result, funds are not blocked in surplus IT assets, and the organization can avail high return on their investments.

3. Proactively mitigate security risks

Organizations across the world are embracing open networks. This leads them more vulnerable to security risks than ever before. Security analysts explore machine log data to identify potential risks that are lurking in your organization. They examine the data for any security loopholes, and if found, such gaps can be further analyzed and closed. This makes sure that your operations are never being compromised.

If this had you wondering, how you can possibly examine the massive machine data from multiple systems and spot that security leak – don’t worry. There are tools for that! These tools work as your faithful assistant to offer you a helping hand. The machine data analytics tools automate the tedious work of converting raw machine log data into information that you can actually use.

Analyze your machine data to discover trends and unleash the undiscovered insights by downloading Motadata with a 30 day free trial.