Welcome to the era of intelligent, self-driving software. Just as self-driving vehicles are set to transform motoring, self-driving software promises to transform our productivity, and strengthen our analytical abilities.
Perhaps you drive an automatic car today—how much are you looking forward to the day your car will automatically drive you? And how much more preferable would smoother, less time-consuming journeys be—always via the best route, with fewer hold-ups, and automatically avoiding unexpected road congestion—where you only have to input your destination? The technology is almost here, and similar advances are driving modern business applications.
AI and machine learning are finally coming of age thanks to the recent advances in big data that created—for the first time—data sets that were large enough for computers to draw inferences and learn from. That, along with years of SaaS application development in cloud computing environments, means that autonomous technology—harnessing both AI and business intelligence—is now fuelling self-driving software… for both cars and cloud applications.
Autonomy—beyond automation
Automation has, of course, been around for years. But autonomy—running on AI and machine learning—takes it to new levels. Today’s software is truly self-driving—it eliminates the need for humans to provision, secure, monitor, back-up, recover, troubleshoot or tune. It upgrades and patches itself, and automatically applies security updates, all while running normally. Indeed, an autonomous data warehouse, for example, can reduce administration overheads by up to 80%.
Intelligent thinking
But the greatest value is perhaps in what AI enables you to discover from your data. When applied to analytics, it can identify patterns in huge data sets that might otherwise go unnoticed. So, for example, you could apply AI to sales data to identify trends—who bought what, where, when and why?—and apply those to improve the accuracy of your future forecasts.
Alternatively, if you were looking for a vibrant location for new business premises, you might use AI to search for an area with a strong social media buzz around its restaurants and bars. You could teach the software to look for specific words or phrases, and harness machine learning to improve results over time.
AI technology is already widely used in HR to take the slog out of sifting through huge numbers of job applications. As well as being faster and requiring less manpower, it’s able to remove both human bias—critical in the highly subjective area of recruitment—and also identify the best candidates based on factors such as the kind of language they use.
Knowledge and power for everyone
These technologies are coming online now—today—for everyone. In the past, most database reporting was typically run by data analysts or scientists to update pre-existing dashboards and reports. Nowadays there are many more business users who are demanding access to such insights, which is being made possible by tools that are far easier to use.
Anyone can experiment with large samples of different data sets, combining multiple data formats—structured and unstructured—and discovering new trends. They can get answers in context, at the right time, and convert them into simple-to-understand insights, enabling decisions to be made more quickly for competitive advantages.
Smarter and smarter…
Yet it’s the strength of those insights that’s really compelling. As one commentator observed: ‘Machine intelligence can give you answers to questions that you haven’t even thought of.’ The quality of those answers—and their underlying questions—will only improve over time. That’s why it’s becoming a competitive imperative to embrace the power of intelligent analytics to ensure you can keep pace with market leaders.
Discover how…
In my last blog, I shared how organisations can profit from data warehouses and data marts, and how Oracle’s self-driving, self-securing, and self-repairing Autonomous Data Warehouse saves resources on maintenance allowing investment in data analytics.
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