How Big Data is transforming the world of Artificial Intelligence
The business has changed a lot in recent years as big data continues to disrupt entire industries. We are seeing top players putting data at the center of their business. So, the question that companies have started to ponder is how do we make big data even more beneficial? That’s where artificial intelligence comes into play. Both big data and artificial intelligence have started to merge, creating an even more powerful data strategies that brands are using to gain a significant advantage over their competitors. The good news is that this innovative technology is still in its earliest stages, meaning that it’s still fair game for everyone. Experts are finding ways to utilize big data in artificial intelligence systems to create robust marketing systems.
While AI and big data are two entirely different technologies, innovative companies are starting to use them to drive each other. The result is that businesses have created a new powerful tool – one that industry leaders can no longer afford to ignore.
Artificial Intelligence has boosted the power of big data
As we learned in the previous section, big data has opened a whole new set of opportunities for businesses, and artificial intelligence has expanded on those opportunities even further. One of the biggest problems that companies experience with data is that they are overwhelmed by the sheer volume being funneled into their systems. So they end up having problems using data to make informed decisions because they are flooded with it. That’s where artificial intelligence becomes a godsend. This technology can automatically filter, sort, and send out essential data to the right people.
Using big data in artificial intelligence has become the latest business trend. We see these two different technologies empower each other and discover essential information on their own through a process called machine learning. Essentially, AI removes all of the flaws that come with the human interpretation of data. Machines are more accurate and don’t let emotion or bias get in the way of sorting data. It’s all done logically.
Big Data creates global diversification
Every day introduces us to more advanced levels of technology, and as a result, the prices of specific systems start to drop. As this happens, smaller businesses can begin capitalizing on these crucial changes. We’ve always seen the big players take advantage of big data because they were the only ones who had access to the right data. That has all changed today! Users are sharing their information everywhere on social media. Since data is easy to gather, systems used to process; it has gotten much more affordable. So what we’re seeing is the diversification of businesses across all industries.
Big Data and AI vastly improve business insights
Before big data was a mainstream business solution, most small businesses had no idea where to find their target market. Small business owners had to rely on their intuition and hope they got lucky. Sure, some people did get lucky, or they paid attention to specific markets to find ways to wiggle in, but this is not a recipe for success. The reason that 90% of businesses fail today is that they are still relying on arcane business practices rather than data. Using big data in artificial intelligence allows companies to build their foundation on powerful business insights rather than sheer luck. The recipe for success has changed.
Artificial Intelligence goes hand-in-hand with Big Data
Pattern Recognition: Machine learning uses this type of system to identify specific patterns in data. As a system processes more data, it will learn and adapt in a way that improves its ability to recognize these patterns.
Bayes Theorem: This is used to estimate the probability of a specific event based on pre-programmed conditions. In business, we use this to provide insight into whether or not customers might be interested in a new product based on their historical patterns.
Anomaly Detection: We use AI to detect anomalies in data that can be used to determine whether it must be used in the analytical process.
Graph Theory: Graphs express relationships through nodes and patterns. These patterns are used to determine specific relationships between datasets.
Transformation of Big Data in Artificial Intelligence
One of the most notable changes that we can see with artificial intelligence is that technology now has a higher computational capacity. In the past, the computing systems required to manage this amount of data would have been much too expensive for small businesses, so it was always just out of reach. Today these systems have become much more affordable.
As a result, even small businesses can use a data-centric approach. Instead of only having access to small datasets and then making decisions based on those small samples, companies can now develop systems that automatically discover trends and incorporate predictive analytics.
Enhancing the customer experience
Big data and AI are working in combination to revamp the entire customer journey. We’re seeing customer services respond faster because personnel has access to information in real-time. These systems can identify common problems and provide quick solutions which are later relayed to customers.
Businesses can also use this data to create predictive models that are then used to market directly to customers. They gather information on social media and AI systems that help identify key patterns. Customers see an improvement in their entire journey.
These systems are also able to leverage social media, a place where everyone under the sun shares information. AI then uses specific targeting strategies to determine how to best approach a customer.
The point that I’ve tried to make in this post is that big data in artificial intelligence has taken on a massive role in today’s business world. We see that it completely changes the landscape in industries like healthcare, finance, and engineering. Companies can get better results at a much faster rate while removing the guesswork. If you are not sure where to start, then consider finding a data processing service that can help you get the ball rolling.
This article was originally published on roboticsBiz. Republished with permission