Log File Analytics

Looking at log files from company web servers to discover opportunities for raising revenues and reducing costs.

Companies today use one or more technical systems in their operations. Examples include web and email servers, point of sale, shipping and customer service systems. Every machine or device has the ability to generate data or create “logs” about its operation. In addition to knowing if the different parts are working properly, companies can analyze all of this data in order to understand how efficient their business is really running.

There is an additional dimension to this problem. In addition to verifying the uptime and safe and proper functioning of technical systems, companies can use log data to discover unknown risks and opportunities. When companies make large investments into technical infrastructure, it is smart to comprehensively examine the different ways that it can be used to help the company earn more revenue, get more done, explore new opportunities, and eliminate or mitigate risks.

The problem, therefore, that log file analytics addresses is a two-sided coin: (1) validate that technical systems are working – and help tune them if they are note, and (2) highlight promising opportunities to get ROI.


The foundation for performing log analytics starts with a basis in three well-established disciplines: (1) technology management, (2) statistics, and (3) business intelligence / business analysis.

To start, the actual data files have to be aggregated and transformed into a data store that can be used for various types of analysis. From the data, series of reports and statistical summaries are created. From these reports and summaries, business intelligence and business analyses can be used to discover key evidence or areas that can benefit from deeper analysis. Analytics tools are then used to combine different data and approaches in a way that generates actionable information for the company.

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The main indicators of a successful log file analytics project are that data can be retrieved from the sources (machines and devices) and is properly transformed into the data store. This enables flexible querying of the data. A milestone of the solution is automating the capture of raw data directly into the data store, without the need for regular manual labor. When the data is properly structured, it becomes possible to create a wide variety of visualizations, such as website dashboards and reports, and also to trigger activities based on thresholds, such as emailing administrators if a system component is under performing.


A company with a strong log file analytics process is a company that can be more forward-looking. In addition to being armed with information about running the most efficient, secure, and stable systems, the company benefits from strategic insights – based on the actual activity of their users. This is a boost in capability and confidence for the organization. Log file analytics can help sniff out threats, mitigate risks, and point to ways to deliver more competitive offerings to the market.

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