What is Big Data Analytics?
Another very prominent branch of Computer Science and Information Technology, Big Data Analytics refers to the infrastructure that facilitates data analytics.
An amalgamation of vast data that has been recorded over a long period of time, the importance of Big Data Analytics has become highly prevalent in the field of technology over the past decade.
Collecting heterogeneous data and producing homogeneous patterns from the same is what Big Data Analytics promotes. Since the beginning of the digital age data has been omnipresent. With humongous data being stored on a daily basis, Big Data has gradually taken the front seat in driving technology ahead.
Intertwined with Data Analytics, Big Data presents patterns that are noticed over a period of time and perhaps produce a set of analyzed data in order to help organizations categorize their data efficiently. The rise of technology can be credited to Big Data that has eventually grown in terms of both proficiency and popularity.
Technologically-driven, Big Data is a reliable source for recording and collecting hefty data that can otherwise be mishandled due to human error. Big Data can be characterized by value (usefulness of collected data) , variety (heterogeneity of collected data), velocity (speed of data collection), veracity (truthfulness of collected data), and volume (amount of collected data).
What is Artificial Intelligence (AI)?
An advanced field of Computer Science, Artificial Intelligence (Al) is a branch wherein human intelligence is manifested in technological machines to perform human functions. As the technological industry is growing at a fast pace, the artificial intelligence future will further accelerate technological advancement in multiple directions.
Ever since the digital computer came into existence (mid-1900s), it has been constantly researched upon that computers can carry out functions that require human functions to stimulate tasks. You can check History of AI here.
Over the years, AI has advanced on a large scale owing to the tireless efforts that have been contributed by technological scholars and experts that advantages of artificial intelligence are accelerating toward success.
Even though there has been no machine that can match the capability of a human, still AI is being regarded as the break of a new dawn in the realm of technology. The evolution of AI in business and other fields has proven to be extremely important.
From the healthcare industry to gaming industry, AI is doing wonders as it continues to perform some of the most multi-tasking functions that earlier could have been performed by humans only.
(Most related: AI in healthcare)
In the contemporary world, AI is everywhere. Being present in restaurants, cinema halls, security checkpoints, etc. Ai is the future of the coming workforce. Yet there is no doubt that human potential can ever be replaced by machines that function on the basis of AI.
How is Big Data Analytics related to AI?
The humongous presence of data was an issue back when Big Data Analytics and Artificial intelligence stayed apart. Since Big Data only supported data collection, filtering of data became a huge issue.
So, Big Data Analytics had to be supported by another field of technological advancement that could filter data for the collection process by Big Data Analytics. That's when Big Data Analytics and Artificial Intelligence came together and collided!
The advancement of AI has led it to occupy an eminent position in human tasks that can help it to collect information, segregate, and categorize the same accordingly. While Big Data Analytics could only store data collected from various sources, AI could further help to filter the infort and pass on the required content.
For instance, when an organization wants to collect data from its website and store it in one place, it uses Big Data Analytics to store data and collect it. Now, when the organization wants to fetch just the blogs of the website, AI will help the organization to do so. Together, AI and Big Data Analytics work well.
The use of AI algorithms that are extremely helpful in promoting the use of Big Data Analytics has become very useful in recent times. The storage of data in earlier times was done by humans. Perhaps human error and frequent mistakes were always present in such a process.
Therefore, the coming of Big Data Analytics is what has swept away the possibility of human errors while giving the responsibility of data collection to a technological tool- Big Data Analytics.
However, Big Data Analytics tools were not enough for humans to analyze the data without mistakes. Humongous data demanded undivided human attention which was clearly impossible. Henceforth, the development of AI broke through this door and collided with Big Data Analytics to collect, analyze, and segregate data.
The future of this combination is extremely bright with the constant burgeoning of AI and Big Data Analytics. While Big Data Analytics is like a garage of data, AI is the tool that helps to clean the garage and segregate the data on various grounds.
With various benefits of this combination, the field of technology is only advancing with better performance. But before discovering the various benefits of this combination, we will first read about the functioning of this combination that helps the world to do so much more than just humans could ever do.
How do Big Data Analytics and AI work together?
The working of Big Data Analytics and Artificial Intelligence is a great combination that has only helped the field of technology leap forward. There are various grounds on which the functioning of AI and Big Data Analytics can be explained.
(Must check: Big data analytics with IoT)
However, it is the prime functioning of this combination in terms of data collection and data analysis that helps understand why this combination is one of a kind and so crucial for the field of technology in the contemporary times.
Here is a list of parameters that help one to understand the functioning of Big Data Analytics and Artificial Intelligence.
The duo of AI and Big Data Analytics helps to establish patterns that are noticed over a period of time. As Big Data Analytics is concerned with the collection of data, AI tends to look through this data by analyzing it and ultimately helps in noticing patterns or homogeneous categories.
This function of establishing patterns is one of the topmost functions that helps us to understand the working of this duo.
As AI is fed with data that has been collected by Big Data Analytics, the software tends to chalk out some patterns that have been following over the time. This further facilitates the filtering of data.
Another function that the duo carries out is that of negating anomalies. Anomalies are anything unusual that exist among normal data. As AI tends to establish patterns, it evidently becomes active in detecting unusual information which leads to the negation of anomalies.
Furthermore, this leads to the cleansing of data that can otherwise be full of unnecessary information. As Big Data Analytics is helpful in storing data, AI leads the chain by noticing things that are unusual or simply different from the otherwise normal bits of data.
When it comes to the working of this duo, negating anomalies is one of the most important functions that AI and Big Data Analytics together perform.
The third function that the combination of AI and Big Data Analytics carry out is that of producing algorithms. While Big Data Analytics collects and stores data, AI feeds itself with this data that helps it to produce advanced AI algorithms in accordance with the data collected.
By establishing patterns and negating anomalies, AI instantly recognizes and forms certain algorithms that help it to segregate the data from the next time onwards. The technologically advanced tool of AI is all that has helped Big Data Analytics to become widespread in global operations.
Benefits of AI and Big Data Analytics
Here are a few benefits of big data analytics and Artificial intelligence:-
Better Customer Service
The first and foremost benefit of AI and Big Data Analytics working together is that it helps the organizations to have better customer service.
As this duo helps in data collection and data analysis, various organizations can implement this duo and improve their customer service. For instance, many organizations have set up AI-driven systems to help customers register their feedback.
This, in turn, promotes the organization to work on the analysis they obtain from AI softwares and indeed search for customer service improvement strategies.
Demands Less Labor Inputs
There is no doubt that the topmost benefit of this duo is that it reduces the burden on humans. Demanding lesser labor inputs, AI and Big Data Analytics together work wonders and have actually led to the minimization of workforce.
As more and more AI machines have come to analyze the data efficiently, more and more humans can stay away from these responsibilities. Yet it should be noted that humans still matter when it comes to this duo and hence, humans can only be disburdened but not wholly disbarred.
Verified Data Analysis
Another benefit that the duo provides is that it always produces verified data analysis. Even though humans have come to believe that they can produce error-free work, there can still be multiple mistakes that can obstruct the veracity of data.
On the other hand, AI and Big Data Analytics are the tools that produce guaranteed verified data analysis. This benefit alone makes this duo so helpful that it is eventually becoming more and more popular.
The potential of AI and Big Data Analytics is that it can predict future data and records. While the duo collects and analyzes data, it can also predict future data that is another milestone benefit.
There are very rare tools that can help predict the future, yet, though the predicted data is only a possibility, it still can highlight the major possibilities in the coming future.
To sum up, I would again reiterate that the combination of Big Data Analytics and Artificial Intelligence is immensely helpful in technological advancement in society.
As the two concepts help in data collection and data analytics respectively, they have given rise to many eminent algorithms for effective data analysis.