The use of Artificial Intelligence in Big Data
21st April 2021

Artificial Intelligence has come a long way since its inception. More and more, AI is making a difference in the modern world - especially in business, where it’s being used in a variety of ways from recruitment to market prediction.

While many companies are still debating the advantages and disadvantages of AI, there are many others wanting to get immediate benefits from these strides in technology. In fact, 72% of business leaders believe that AI is going to be a fundamental business advantage in the next few years.

Right now, AI will be especially invaluable to businesses looking to harness the power of big data to analyse performance and make decisions. Here’s how AI is making data analytics easier, and how it’s changing the job market as it becomes more and more prominent.

The rise of AI in data analytics

With the data economy being more prolific than ever - worth an estimated $79 Billion USD and supporting 1.65 million jobs - keeping track of the vast amount of data that helps to understand healthcare, transport, finance and property industries is more difficult than ever. Gathering data manually is a formidable and mundane task: not only is it exhausting resources and time, but this process of data mining can be so strenuous that we forget some of the important tasks regarding data analysis and strategy.

With the integration of artificial intelligence, datasets can be analyzed in a way that a human worker can’t. Where a human being might be able to analyze hundreds or thousands of items of data, a machine can analyse thousands or millions of items in just a short time. A full team of well-paid analysts take weeks to complete a task, with an added element of human error. A machine could take a minimum of a few hours and a maximum of a few days - but be entirely without error.

Is AI making human analysts irrelevant?

This ability to assist in data analysis has meant that the use of AI within data analyst roles has risen by almost 2000% since 2009. AMPLYFI’s AI DataVoyant Platform has revolutionised the way AI can be implemented into data analyst roles. It was able to analyse over 50,000 documents and discovered the most common skills within the “analyst” job role from 2009 to 2019.

By narrowing down what skills were common, the AI research was able to point out what was lacking. The research uncovered that there was a marked rise in a need for business skills (up 76% in the last five years), problem solving (112%) and verbal communication skills (19%). Microsoft Excel (-49%) and data analysis (-16%) have fallen appreciably.

However, AI isn’t condemning humans to irrelevancy. Free from the more menial aspects of data analysis and mining, humans may now spend their time developing solutions and ideas around the data analysis procured by artificial intelligence. In fact, the use of AI will only make the role of a data analyst more necessary in the years to come.

Data scientists can now optimize AI processes and apply human creativity to an AI lead world, using their technical skills and social skills to apply creative problem solving, communication and collaboration to solve issues from a variety of angles. With the AI doing the busy work, data scientists can innovate and collaborate.

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