What is Diagnostic Analysis; Steps to do this?

What is Diagnostic Analysis; Steps to do this?

When it comes to modern technology, there are threats lurking around everywhere, and despite all the security checks and special infrastructure in place, you can never be too sure about the threats and vulnerabilities that exist. And then comes the breach or a cyber incident which literally grasps the working edge of your business from the throat and start compressing.

No business or company no matter how astounding can ever fully recover from a cyber condiment in a matter of days. It takes time, patience and specific expertise to pull through it. On the other hand not learning what caused the attack in the first place and driving blindly is another factor that undermines the security of the organizations.

This is where the concept of diagnostic analysis comes into play to find out why did a security breach happen? If some of you are not that acclimated with the term then here is a brief description of it right here;

What is diagnostic analysis?

The diagnostic analysis is a special type of analytical technique using which the data s interpreted and analyzed properly to find out what happened or caused a particular cyber breach. There are various different techniques that are used for the sake of understanding or extracting data for it to be analyzed properly. Some of these techniques include; drill-down, data discovery, data mining, and correlations, while all of these might be used it is not incumbent to use all of them for the sake of performing diagnostic analysis. Every dedicated breach might have something different principle on which it works but might not necessarily use all of these techniques.   

The cause of the events with proper time stamps and behavior of various systems is analyzed which not only clarifies as to why the breach occurred but also using what specific techniques did it occur is also revealed.

Benefits of the diagnostic analysis

This technique first of all would help you greatly in order to understand the kind of questions like what is going to happen in the future regarding updates, the overall operational setting of your place, and others. This is merely done by interpreting tons and tons of raw data and faster too which will help you to answer various critical workforce-related questions. Furthermore, deep insight into the working behaviors of the employees can be studied and actionable insight can be retrieved. Although the list of benefits can go on and on but let’s study the steps involved in the successful implementation of the diagnostic analysis.

All there is to know about Diagnostic analysis process

First of all, an IT-based organization must form various KPIs or otherwise known as key performance indicators which tells us all about the current operational stats of the organization. Establishing those PIs would help an organization to derive a data-driven decision whenever necessary which will help in the identification of the latest key trends, thresholds, anomalies, and other different things including the very reason for a particular cyber breach. In reality, many business intelligence solutions are keenly bent over using the diagnostic analysis techniques for the sake of measuring their current rate of success, what are the current letdowns, and various other things as well.   

Knowing what happened is eventually the reason which will help you to understand the reasons that led to a particular cyber breach but it is not enough for making a confident decision and settling on a particular aspect of things.

There are following three practical categories that fall under the impression of diagnostic analysis OR it can also be taken as the key steps for performing the diagnostic analysis in its right capacity of the process;

Identifying of anomalies

The diagnostic analysis is necessary for the sake of identifying and interpreting data the best it can for making calculated decisions regarding the future stats because it can’t be done by simply looking over the data. For example, it could help you to apprehend things such as why the sale of a certain product or service has increased while there was no significant increase among the marketing practices at all.

OR on another note why the traffic on a certain website did has doubled without any practical cause. Asking these questions is necessary to identify what kind of anomalies lurk behind the curtains and what the data is suggesting.

Drilling into the analytics/discovery

Analysts must try their best to find about the original sources of the data that will practically help them in explaining why a certain anomaly happened. In general, it requires the professionals to look for the practical stats of data outside the current data sets because it will help them to pull in the data from external sources to determine the correlations and then examine if any of them are casual or not. It is a giant leap for configuring whether or not the breach that occurred was a result of the onboard individuals such as from within your organization or it happened simply outside of the organization's reach with no special ties to anyone within your organization.

Determining of casual relationships

Hidden relationships between several anomalies can be determined by looking at the very events that resulted in a cyber breach. Hidden stories in the data can be easily covered by using the diagnostic analysis of the data at hand but in no capacity can this data be used for the absolute verification of the theories many professionals might have about a particular incident. Diagnostics and brief analysis of the data should be done first in order to accept any trivial decision that lingers after the inspection has concluded.

The scope of the diagnostic analysis is currently progressing but isn’t that far fetched yet because simply many organizations and businesses still to this date use the traditional methods of inspection and diagnostics but there is some hope in the future.

Job roles and salary of the diagnostic analysis involves these professionals working closely with the data scientists and engineers to determine the root cause of a particular incident. Although the average salary of these professionals is expected to be somewhere at $145000-$186000.

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