Today we are living in an era of the digital revolution, which is driven by data. This data is generated and processed in huge quantities. As data grows in strength and numbers, the role of Business Intelligence will also increase. Data will come to play a more critical role in making decisions and handling business processes. This is where machine learning will play a key role.
As modern businesses increasingly look to use analytics, machine learning will drive BI, allowing employees to independently analyze the data they need and gain insights from it while leaving the more advanced tasks to expert analysts. This, in turn, will help companies to understand market trends better and accordingly take quality decisions to achieve competitive advantage.
In this article, we will discuss a few prominent ways in which machine learning is changing the BI landscape.
Enhancing Fraud Detection / Early Warning Systems
With each passing day, online criminal activities are increasing. This is a real danger, for there are thousands and thousands of sensitive data on servers across the world. All these face the risk of a sudden cyber-attack or a fraudulent activity that can result in the loss or stealing of precious data. Several businesses have found themselves as the victims of cyber-attacks resulting in the loss of several billions of dollars and brand reputation.
Only prompt prevention and early detection can thwart such nefarious activities, minimize losses, and reduce the risk of frauds online. AI-driven systems propelled by machine learning can help detect and prevent frauds easily and more consistently. They can spot out suspicious activities online and system vulnerabilities and suggest the best remedies to negate them.
Producing Cleverer Digital Assistants
Digital assistants today come in various shapes and sizes, with a vibrant presence in most industries. Though they are termed as AI-driven systems, in hindsight it is machine learning, which is driving AI-driven systems and making them smarter.
Machine learning is enabling all digital assistants to use natural language processing to understand what people say and want, and accordingly, deliver the best results that meet their needs. It is also enabling AI-driven technologies to adapt to people’s preferences, adjust to the patterns in their behavior, and finally, generate worthy long-term results.
Facilitating Automated Language and Image Translation
Translation technology today is more refined and sophisticated thanks to AI and machine learning algorithms. A good example of this development is Google which is continuously upgrading its instant image translation. Today, it helps people to translate words from any kind of image by using their camera. All of this is done in real-time. Google uses predictive analytics propelled by machine learning to achieve this feat. Google has also come up with a machine learning advancement that forever changed the way people looked at foreign languages.
Machine learning enables the analytic tool to swiftly understand and adapt, create better translations, and above all, minimize translation errors while at the same time enhancing UX. Also, Google makes it possible to comfortably and accurately translate images from written content from any language.
Improving Customer Support
AI through machine learning has been enhancing the level of customer support for the past many years now. One good example of this is chatbot technology which is today able to handle mundane queries and tasks. Many companies are leveraging AI with machine learning to alter their customer-support delivery concept and deliver a data-driven customer experience.
Machine learning helps companies to adopt an omnichannel approach to customer experience and obtain data from all customer-service channels. Also, it can be used to analyze all customer interactions and personalize customer relationships. This, in turn, helps companies better engage their customers online and in-store and improve their level of customer service, customer retention, and customer acquisition.
Today’s machine learning models are more sophisticated and very effective at unearthing hidden patterns and insights in data. For some years now, data specialists have been utilizing these techniques to handle and solve complex business issues. Better advances in machine learning’s processing power have made the development and running of even complex mathematical models more accessible. As a result of this, a growing number of BI vendors are incorporating machine learning capabilities into BI tools, thereby making BI more effective at spotting out hidden insights.
With further automation of the process, insights can also be delivered much faster. This will also free up analysts to focus on more relevant tasks of high value while businesses with better information can react swiftly to changing scenarios.
Conclusion
Machine learning is not only changing the BI landscape but is also revolutionizing every industry in the world. If you would like your business to leverage the power of machine learning in BI, then align your requirements with Altusmeus, a global niche IT talent acquisition provider. The company offers high-tech services to different industries.
