How Log Files Can Be Used for Business Analytics
Business analytics is a practice that can be of great use to dynamic and data-driven companies. Logging, more often than not, is an afterthought for many companies. In this article, we’ll cover just how vital log data can be when used effectively for business analytics.
Business analytics is a practice that can be of great use to dynamic and data-driven companies. From legal and finance departments through to sales and marketing, thorough analytics can unveil hidden patterns and opportunities that, if utilized correctly, can help a business grow. The more data your business has to analyse the more useful information you’re going to get. However, logging, more often than not, is an afterthought for many companies.
A log file is a computer-generated registry that contains detailed information about events, patterns, activities, and operations that relate to a specific executable or server. Most log files are saved in plain text format, which makes them harder to read and analyse manually.
What is Log File Analysis and How it Works
Log file analysis is the process of taking data collected from various resources, on your device or server, to find patterns and detect anomalies. In other words, it’s the turning of pure data into tangible information that helps you make the right decisions. Logs are supplied as different types, depending on their source; from OS logs to application logs, warning, and error logs. When the files are collected for analysis, they’re converted into the same format, saving time and limiting analysis errors.
However, converting all log files into the same format alone is not enough. Because they came from different sources, and sometimes different devices, analysing them can be too complex and drive inaccurate results, even when using specialized software.
Mainly, there are five processes raw data logs need to go through to become tangible:
- Log Normalization — Data from different sources needs conversions and re-scaling, so it matches the other logs. Fixing date formats, for example.
- Tagging — Tagging categorizes data that fits specific criteria using a keyword, to simplify filtering when displaying it.
- Patterns — Finding patterns is key to finding anomalies that might be worth checking out.
- Artificial Ignorance — Artificial ignorance is a way to filter out useless data from logs. They’re usually routine system updates and notifications that show no sign of abnormality.
- Log Correlation — Similar to pattern recognition, log correlation works on finding relations between multiple logs instead of one.
While keeping detailed logs can be a helpful reference in the future in case of an event, they are ideal for running numerous detailed business analysis as they can be used to:
Security is one of the most important aspects of a business. Without proper cybersecurity, it’d be near impossible to gain the trust of clients and investors. Since logs collect data from all endpoints and executables, analysing them enables you to catch suspicious behaviour, find holes in your security system, and prevent zero-day attacks.
In case of a security event, whether it was caught immediately or long after, logs can help determine precisely what happened from the precise location of the breach to the parts that it affected.
Web logs, for example, help prevent DDoS attacks, where the attacker floods your website with traffic to break the hosting server, making it inaccessible for legitimate users. Logs catch their IP address, and analysis can detect threats in real-time.
Improve Marketing and Sales
Sales and marketing activities without the use of intelligent data analysis are a game of luck unless you have the right metrics. Analysing website log files lets you track visitor’s movements around it. Giving you insight into what caught their interests and what didn’t. The process also helps with identifying which marketing campaigns worked and which didn’t, depending on successful and failed conversions, and traffic sources.
Analysing all the numbers you get into useful information can help increase your overall return on investment (ROI), while also decreasing the time and resources spent on ineffective marketing campaigns.
Improve User Experience
Having a detailed log of visitor’s movement and activity on your website or cloud-based application can help you create a user experience that best suits your target audience. Simple log analysis can immediately reveal which parts of the site, or even page, visitors mostly focus on, in addition to which they’re least interested in, and whether they have trouble reaching a specific page or feature.
Not to mention, logs register crashes in the server, sending out alerts even before visitors notice them. While thorough improvements and insights might require additional analysis of the logs, it’s worth it.
Error logs, for example, can be traced back to the root cause of the problem. Pinpointing the location of the issue, its effects, and what might have caused it. Also, you can run tests afterwards to check whether the solution worked or just shifted the issue elsewhere.
Keeping and analysing logs of every device lets you know whether hardware performance is up to standard. Storage space, CPU power, and RAM storage that can’t support certain software can cause a myriad of, otherwise, easily avoidable problems. Hardware below the recommended can affect the device’s speed and cause lagging, costing the company time. Also, if the CPU or RAM are past their capacity, the device could crash, resulting in lost data.
Observability and Compliance with Privacy Laws
As organizations increasingly shift more of their services & operations into cloud & hybrid cloud environments, they need to account for local, international, and regional privacy laws. Log files help track the flow of data and its destination, ensuring the network’s transparency and observability. If the network, or system, provides sufficient and accurate data that can be evaluated, the site is considered observable.
The More the Merrier
Raw data is a powerful resource for unexpected findings and in-depth information. While its uses might seem limited when first implemented, the better you’re at looking at it from different angles, and running various operations and analysis, the more data stored in simple log files can deliver. After all, no data is entirely useless.