Data analytics is an action that can be used to process raw data to achieve certain goals. It should be understood that data analytics is also a skill that is quite widely needed as a job opportunity today given its more diverse functions. The results of this data analytics can be used as the basis for decision-making.
One of the applications of analytical data is to improve server monitoring so that it runs more optimally. As for a further explanation of how to use analytical data to improve server monitoring, you can check everything below!
What is Data Analytics?
Before discussing further, you first need to know what is meant by analytical data. This data includes analytical references to information that has previously been entered into a special database so that the results can be used to get more appropriate decisions. There are so many applications that are needed from analytical data now and in the future.
Some of the things that can be done with analytical data are estimating what will become a trend in the future, a reference for decision making and also to increase the efficiency provided. In addition, the answers from this analytical data can also be used to further review current trends.
Likewise with the use of server monitoring, when you combine it with the appropriate analytical data, the company can more easily understand how the business can develop and also what risks might arise. Such a way of anticipation is really good so that the handling process is also faster.
A smooth, glitch-free server can increase the trust of consumers who use it. You can also respond more quickly to what consumers are complaining about without letting them wait longer.
Types of Analytical Data
There are many types of analytical data that can be used to help the process of increasing consumer confidence including in helping to improve better server monitoring. Those of you who are interested in understanding more about the types of analytical data can immediately check the explanation below!
- Prescriptive Analytics
The first type of data analytics that you need to understand is prescriptive analytics which can be used to provide better solutions to problems or concerns. The data that has been analyzed can be used for consideration before making decisions so that it can reduce errors that might occur.
It should be understood that in general, most problem solving is done only based on raw data so that the results are indeed less solutive.
- Predictive Analytics
Besides prescriptive analytics, you also need to know that there is an analysis made in accordance with predictive to answer or predict what will happen in the future. The process is usually related to historical or past data to see the potential for the problem to reappear in the future.
This data is obtained from years of previous data or it can also be called learning from monitoring problems that have occurred. So if one day the same problem occurs, you can more easily handle it.
- Diagnostic Analytics
Diagnostic analytics is used when a company wants to gain insight or experience based on a particular problem. In handling this analysis process, it is used for data search, development and recovery so that the data provided is directly entered into certain analyses and of course more varied.
This analysis is indeed more complex and as a further stage of the analysis that has been done before. In addition, the data from this analysis is also a decision to take the basis for descriptive analysis so that more considerations will be given.
- Descriptive Analytics
The next type of analysis is descriptive analysis which can be used to reference more accurate answers about current events. Because the event is still new, analysis with a more appropriate description can be used to present the interests of more appropriate stakeholders.
Usually in this case they will immediately collect a lot of data from the past to compare with what is happening now. The purpose of this analysis process is to be able to make those stakeholders have an interest in considering the results better.
This reference is also closely related to creating new strategies and also reports that have previously been created as a basis for creating new reports.
How to Use Data Analytics to Improve Server Monitoring?
Analytical data can be used to help improve faster and more accurate server monitoring. So that if a certain problem occurs, you can immediately get a more appropriate solution. In general, analytical data has a quite crucial role in helping server monitoring as follows!
- Automate many functions of a given analysis.
- Direct resources to be more precise on target.
- Helps the process of identifying areas that are more important to improve.
- Helps the process of detecting problems or threats in a timely manner even before they are detected by consumers.
As an illustration to make it easier to imagine how to use data analytics to improve system monitoring, you can immediately check the full explanation below!
- Choose the Metrics Used
The most important step you need to use to support server monitoring is to predict in advance the metrics or thresholds that will be given an alert. The metrics in question are quantitative indicators related to measuring aspects of server performance in it.
Some of the disturbances in question are regarding response time, network traffic, memory utilization and also CPU.
- Visualize and Collect the Data
After that you can directly collect and visualize the power provided by the process of recording, storing and displaying the performance matrix of the server in real and live according to a certain period. There are many tools that can be used to help you customize to your needs and main objectives.
By visualizing your data, you can more easily spot trends or correlations that can be used to predict problems so they don’t affect your performance.
- Interpret and Analyze Data
The third step is the process of interpreting and analyzing data to measure several important analytics ranging from logs, performance testing and machine learning. Analysis of these logs can help with source identification and better performance testing. Interpretation with data analytics can get more appropriate answers.
- Take Action Based on Data
The next step that should not be missed is to use the follow-up data to solve problems or face problems that may occur. The existence of this clear reference can help the data monitoring process to be faster and more efficient. That is a complete explanation of the use of analytical data for more accurate server monitoring. You can use Netmonk’s help for more precise analysis including the application of powerful server monitoring analytics data. The process is also faster with affordable financing every month.
