Did you ever wonder why Big Data and Artificial Intelligence (AI) are so commonly used together? Most Big Data experts and AI developers feel that they are a match made in heaven. How? Read below:
Learning of Blog
- Introduction
- Big Data and AI
- How Big Data Can Help in AI Experiments
- AI Technologies used with Big Data
- Summary
Introduction
Data is getting bigger with each passing day, and manual analysis of large data sets is not an option anymore. For instance, if there are cameras at an intersection record footage 24/7 and for 365 days in a year. This means that if there are 8 cameras at the intersection, there’s 1344 hours and 490560 hours of footage every week and year, respectively. Monitoring such footage (data) is impossible for any human being. Even if someone thinks of hiring people for the job, it won’t be economically feasible. The only viable solution to analyze large data sets is with the help of Big Data and AI algorithms.
Thus, the craze for artificial intelligence certification and big data training courses is on the rise.
Big Data and AI
Big data and AI are known to be the pillars of digital transformation. Many organizations are hoping that AI will revolutionize their organizational data. Machine learning (a subset of AI) is considered to evolve, learn, and improve the algorithms by feeding on input data. Whereas, Big Data helps companies analyze large sets of information and draw resourceful results from it.
If a leather garment manufacturer exports its clothes to the European market and focuses on learning about customer preferences by collecting data from the market. AI can analyze their interests and purchase patterns through the data and improve their collection.
How Big Data Can Help in AI Experiments
Since AI is known to reduce overall human intervention jobs, people think that AI has all the capabilities to eliminate human jobs. The human role is diminished due to the proliferation of AI but this ideology has been changed by the involvement of Big Data. Machines can make decisions based on facts but cannot match human analysis. But with Big Data, data scientists use a hybrid approach involving ML and their intelligence.
So, it is clear that the merger of AI and Big Data will open gates for many new opportunities for companies and individuals to ponder upon. A mix of AI and Big Data can help organizations better understand the interest of customers. By using machine learning concepts to analyze the data quicker, organizations can identify the customer’s interests in the shortest possible time.
How Big Data Can Help in Global Diversification
The world is filled with diverse people with different languages, cultures, religions, etc. People showcase the same enthusiasm when it comes to adopting new and exciting technologies. With the introduction of new technologies, the cost of machine learning and AI tools are also significantly decreasing.
Big data technology and tools help companies deliver relevant solutions according to the customers’ preferences, while machine learning allows companies to deliver solutions, so that customer sentiments don’t get to the heart. As with any woman-oriented product, the way the product is marketed is entirely different in different geographies.
AI Technologies used with Big Data
There are many AI technologies used with Big Data, and some of them are listed below:
Disorder recognition
For any dataset, Big Data analytics can be used if the disorder is not detected. Here you can find fault detection, sensor network, ecosystem distribution system health with big data technologies.
Bayesian theory
Bayes’ theorem helps in determining the probability of an event based on pre-known conditions. The future of any event is also based on the previous event. This theory is best used for analyzing customers’ interests in the product and can be obtained by using past or historical data sets.
Pattern Recognition
Pattern Recognition is a method to detect patterns in a certain amount of data. With the help of training data and machine learning techniques, the practice of identifying patterns and monitoring them can be easily enhanced.
Graph Theory
Graph theory is based on graph studies that use different vertices and edges. Through node relationships, the data can be traced to the linearity and the relationship.
Summary
Businesses that understand the importance of the human and mechanical brain are able to predict the market correctly and grow with the trend. They save time and reduce potential bias, resulting in increased enterprise productivity, quicker insights, and efficient business operations.
If you too wish to understand the concepts of AI and Big Data, check out our Big Data certification and Artificial Intelligence training courses.