Over the next two years, 75% of companies report that they will invest in technology that collects big data. The big data industry has quickly solidified itself as a growing and increasingly essential part of the business environment. But big data cannot help a company by itself; someone or something must analyze the data to get anything out of it.
Manual data analysis takes time and comes with a paradox: the more data a company mines, the more accurate the analysis can be, but the more data mined, the less possible it becomes to accurately analyze. Machine learning provides the answer.
With machine learning, companies can mine data to get the information that puts them ahead of the competition by gaining access to trends and information they would have never gotten before. Machine learning will unlock the full potential in multiple ways.
1. Increasing the Number of Variables
Traditional analysis cannot handle too many variables at once. The analyst must cut down the amount of information in order to make it manageable. Machine learning does not have this limitation. It thrives with complex data from multiple sources, sorting through them with an accuracy and speed that no traditional analysis could achieve. Unlike systems before it, machine learning only gets better the more data is added to it.
2. Getting Rid of Sample Sizes
Normal analysis must use sample sizes. No matter how extensive and great the big data, only a slice of it can be extrapolated from. This always runs the risk that the sample will not be an accurate representation of reality. Machine learning gets rid of this problem altogether. Using all the data available increases the accuracy and makes gathering it worthwhile in the first place. Even real time data can be incorporated, keeping the models constantly up to date.
3. Finding Hidden Patterns
Analysts can be great at their jobs, but they are never perfect. Even with no mistakes, patterns can be hard to find, hidden underneath piles of data that obfuscates what is truly happening. Machine learning can bypass this with its processing speed. The amount of comparisons that can be made with machine learning means that many comparisons of big data can be performed. As the model improves over time, new patterns may be unearthed. Some hide just below the surface, out of the reach of the traditional methods used now.
4. Detect Problems Faster
Analysis takes time, but it takes significantly less time once a company involves machine learning. Because machine learning can be used to monitor real-time data, many time-sensitive issues may be caught before they snowball out of control. Fraud, imminent failure of systems, and unusual activity spikes can be found as they happen. Machine learning means that the system begins to know what to look for and alerts the company when something suspicious occurs. The prior model of analysis could never do this, as human interaction makes constant deep-level monitoring impossible.
Of course, using machine learning to analyze data in real time will lead to increased network traffic. This means more work for the IT professionals in the company. No matter how good the machines get, the devices, services, and traffic on the network will need to be monitored by IT. Thankfully, free tools that help IT professionals monitor the network exist. Microsoft Network Monitor allows the capture and analysis of network traffic to troubleshoot problems. NetworkMiner allows the IT Professional to reconstruct what a user has been doing on the network. Many other such free tools exist. IT Professionals can monitor the network more easily and effectively by researching what best suits their needs.
