Machine Learning (ML) algorithms are designed to automatically build mathematical models using sample data to make decisions. Rather than use specific instructions, they rely on patterns and inference instead. And the business applications abound. In recent years, companies such Google and Facebook have found ways to use ML to utilize the massive amounts of data they have for more profit.
Many data-driven companies struggle with tracking anomalous behavior in their KPIs, let alone their more granular metrics, because traditional BI tools just can’t keep pace with big data. Manual processes, whether monitoring dashboards or setting static thresholds, often leads to missed incidents or prolongs time to resolution.
Getting the right metrics at the right time could be the difference between running a smooth operation and making costly mistakes. And yet, data delays are still very much a part of data analysis today.
The global data supply reached 4.4 zettabytes (ZB) in 2013 – or 4.4 trillion GB – but less than five percent of that data was actually analyzed, according to the seventh Digital Universe report by the IDC. Approximately 22 percent of all existing data would actually be useful if tagged and analyzed.
Success in business hinges on making the right decisions at the right time. You can only make smart decisions, however, if you also have the insights you need at the right time. When the right time is right now, outlier detection can help you chart a better course for your company as storms approach – or as the currents of business shift in your favor. In either case, quick detection and analysis can enable you to adjust your course in time to generate more revenue or avoid losses.
5G is here and is widely expected to be a transformative communications technology for the next decade. This new data network will enable never-before-seen data transfer speeds and high-performance remote computing capabilities. Such vast, fast networks will need dedicated tools and practices to be managed, including AI and machine learning processes that will ensure efficient management of network resources and flexibility to meet user demands.
