Big Data and AI are two of the most popular and useful technologies today. Artificial intelligence is in existence from more than a decade, while Big Data came into existence just a few years ago. Computers can be used to store millions of records and data, but the power to analyze this data is provided by the Big Data.

We can say that together Big Data and AI are set of two amazing modern technologies that empower machine learning, continuously reiterate and update the data banks, and taking the help of human intervention and recursive experiments for the same. Today, we have brought this blog to provide informational usage of AI and Big Data together to resolve all possible issues related to the data.

Big Data and AI

Big Data and AI are considered two mechanical giants by data scientists, or other big corporations. Many organizations consider that AI will bring the revolution in their organizational data. Machine learning is considered as an advanced version of AI through which various machines can send or receive data and learn new concepts by analyzing the data. Big data helps the organizations in analyzing their existing data and in drawing meaningful insights from the same.

Here, for example, we can consider a leather garment manufacturer that exports its garments to the European and do not have any idea about the customer interests than just by collecting data from the market and analyzing it through various algorithms, the merchant can identify the customer behavior and interests. As per their interests, they can provide the cloths. For this, the algorithms can help to find insight and accurate information too.

How Big Data Helps in AI Experiments

As it is known that AI will reduce the overall human intervention and jobs, so people consider that AI has all Machine Learning capabilities and will create robots that will take over human jobs. The human role will be reduced due to AI expansion and this thought has been broken and changed by the involvement of the Big Data. As machines can take decisions on the basis of facts but cannot involve emotional interaction, but due to big data the data scientists can involve their emotional intelligence and take the proper decisions in the right manner.

For a data scientist of any pharmaceutical organization, he cannot only analyze the needs of customers but also inhibit the local rules and regulations of the particular market of that region. Depending on the salts used in any medicine, they can suggest the best options for that market, while in case of machine learning it may not be possible.

So, it is clear that the merge of AI and Big Data cannot only involve the talent and learning simultaneously, but also give rise to many new concepts and options for any new brand and organization. A mix of AI and Big Data can help the organizations to know the customer interest in the best way. By using machine learning concepts, the organizations can identify the customer’s interests in minimum possible time.

How Can Big Data Help in Global Diversification?

With every passing day, the new technologies and tools are introduced in the market so the cost of tools of machine learning and AI are also reducing significantly. As a result of a price drop, the technology will be adopted by a number of organizations. Even in a global region with diverse culture, language, religion, the technology and tools will be adopted with the same enthusiasm. At the same time, the provider will have to provide the equivalent solutions to the market as per the customer needs.

Big Data technology and tools will help the organizations in providing the relevant solutions to the customers as per their region and language, while at the same time machine learning will help them in providing the solutions to the organizations in the way so that customer sentiments will not get a heart. Like for any women-oriented product, the way to market the product will be entirely different for Sri Lankan and Iranian markets as the sentiments of the women of both the regions may be entirely different.

Big Data and AI to Boost Market Analysis Insights

Right now, the market of Big Data and Artificial Intelligence in their novice state and service providers do not have any idea where their customers are exactly and what are their needs? With time, they will realize the exact customer requirements and plan the offers and product functionalities accordingly. With time, organizations will realize that what are the exact needs of their customer requirements? Even AI-based solutions may need to undergo huge changes as the customers' requirement may vary.

AI Technologies that Are Being Used With Big Data

There are several AI technologies that are used with Big Data and below-listed are a few of them:

Anomaly Detection

For any dataset, if an anomaly is not detected then Big Data analytics can be used. Here fault detection, sensor network, eco-system distribution system health can be detected with big data technologies.

Bayes Theorem

Bayes theorem is used to identify the probability of an event based on the pre-known conditions. Even the future of any event can also be predicted on the basis of the previous event. For Big Data analysis this theorem is of best use and can provide a likelihood of any customer interest in the product by using the past or historical data pattern.

Pattern Recognition

Pattern recognition is a technique of machine learning and is used to identify the patterns in a certain amount of data. With the help of training data, the patterns can be identified and are known as supervised learning.

Graph Theory

Graph theory is based on graph study that uses various vertices and edges. Through node relationships, the data pattern and relationship can be identified. This pattern can be useful and help the big data analysts in pattern identification. This study can be important and useful for any business.

Summary

It can be said clearly that AI and Big Data are two of the emerging technologies that are used by organizations extensively. Even the technologies are used by them to provide better customer experience in an organized and smarter way. The technologies can be blended to provide a seamless experience to customers.

AI and Big Data use many methods and techniques, but they can be used in an integrated manner and provide a result to be used by the organizations to analyze customer interests and offer them the best-optimized services.