Impact and importance of big data and AI in today’s world

AI and Big Data are very commonly used these days and everyone is talking about that. They are in trend because they lead to Hyer automation.  They both work with the same aim of making maximum use of the data and it is trending because it is accelerating the work in IT industries on a massive scale.

The Topic Covers

  1. Benefits of AI

  2. Usage of Machine Learning

  3. Big Data: Overview

  4. AI vs ML vs Big Data

  5. AI, Big Data & Machine Learning

  6. Conclusion

 

Benefits of AI

Artificial Intelligence in simpler terms is a computer system having human intelligence to perform tasks which used to be performed by humans. AI is in trend now as it is providing significant number of benefits to the industries. It’s majorly useful in the repetitive tasks which used to be done by humans initially and because of AI, humans can now invest their time and energy in more productive activities than doing mundane work as it saves manpower and human energy. AI is also beneficial in decision making as AI can analyze the patterns more quickly and smartly than humans which can help in better servicing without any mistake or chances of error. As AI is better in analyzing, it can interpret the most complex data and huge amounts of data by making the smallest data into use, which ultimately helps in improving experiences to the end users and company’s goals.

Humans depend on industries for their living but because of AI humans will program computers and robots to work for themselves without needing to move a single thing by themselves. AI is also creating huge Unemployment issues as all the work has started done through AI these days which reduces the need for humans to work in a company as it is cheaper as well.

 

Usage of Machine Learning

Machine Learning is also very trendy and basically, it’s a part of AI which involves usage of software applications to estimate accurate outcomes without being programmed to do so based on past data and experiences. It is highly beneficial to reduce the workload on a large scale as it predicts the outcome and more importantly trends and patterns followed in any field way faster with the available data. It also helps in saving time for companies. But a coin always has two sides, so there are limitations as well of Machine Learning like ML completely works on data, and some data keeps on changing on regular basis depending on the factors so we have to wait for processing of the new data. And as a result, it breaks the chain of continuity as processing needs time and if not processed, results can differ between new data and old data.

 

Big Data: Overview

Everyone is talking about Data these days as “Data is new Oil” after all. The larger the data the larger will be the benefit an industry can have from it, which gives rise to Big Data. Big Data is the collection of extremely complex and large datasets which is used to gain insight into associations to improve decision making and strategy. Opportunities in Big Data are substantial like Big Data can glean data from many sources so that a business can target advertising directly to potential customers who have shown interest in their products by internet searches. But Big Data also has challenges like Personal Privacy as there is concern about all the data being available to marketers in real time having the risk of infringement of civil rights in the case of governmental use of big data. As there’s a huge amount of data, it needs to be organized for its optimum use and for analysis which is mainly done by data analysts. AI improves the capability of data analytics by focusing on the smallest detail. That’s how AI and Data Analytics can change the game as with every single detail the overall pattern for future trends can differ. Data can be organized mainly in 3 ways: Structured, Semi-structured and Unstructured.

 

AI vs ML vs Big Data

AI vs ML vs Big Data is an important topic for discussion. AI is a broader aspect which includes ML and ML needs data to perform its functions, that’s how they are interconnected. If anyone is removed then the remaining becomes meaningless. Big Data is mainly the analysis of information from massive volumes of data whereas Machine Learning is using input data and algorithms to understand future trends and patterns whereas artificial intelligence is for using those trends and do better decision making without error.

 

AI and Big Data

AI and Big Data go hand in hand as the more data AI will get, the better the AI will perform in predicting the outcomes and providing information. That’s why big data influences the rise of Artificial Intelligence in companies, because of which each company is focused on collecting more and more data in order to sustain and perform well. None the less, big data can’t function alone as it needs to be analyzed in order to give results and AI also can’t function alone as it needs data to give results, which clearly states that there is no AI or Big Data or AI VS Big Data as both are equally important in the AI journey of the business and gives impetus to rapid modernization.

 

Machine Learning and Big Data

Machine Learning and Big Data also works hand in hand as with the help of big data machines respond accurately which ultimately leads to better service quality, better relationships with customers and better business operations. As there’s a variety of data available it becomes easier to predict outcomes, which also helps in covering a large amount of audience and target marketing. Hence Big Data, Machine Learning and Artificial Intelligence has one thing in common that they all are data driven things and data is the key to enable them to perform.

 

Conclusion

There are many benefits of AI and ML in it and it is very helpful in all areas. Like AI should be used in those areas where manpower is wasting or where the work is tiring or in those work which are essential but no one wants to do it like manual scavengers so that we can protect their dignity. ML is also beneficial as it predicts the trend which helps companies in target marketing. But they need data in bulk to perform and data always has a risk of invasion of privacy which is a very serious concern.

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