When Big Data and Artificial Intelligence Complement Each Other

The problem with Big Data is that there is too much of it. Analytics shows that data is growing at an almost exponential rate. This number is not surprising, especially when you consider the growth of machine-generated data. VisualCue analysis shows that stored data will increase to 44ZB by the end of 2020 and there are 2.5 trillion bytes of data generated by people around the world on a regular basis, according to IBM. It takes too many personnel if humans have to analyze data generated by companies, individuals, and machines, which is not economically feasible. Get more info from computer vision datasets.

This is where Big Data and Artificial Intelligence work together. Managing this huge amount of data using AI software algorithms is the only way to work effectively with Big Data. Big Data and AI work in tandem. Through machine learning, these two modern technologies, (Big Data and AI) have formed an impressive pairing to provide computing processes on a whole new dimension by leveraging continuous data looping processes with minimum human intervention.

While Big Data and Artificial Intelligence complement each other, here are some areas where they work well together.

Big data and AI work best at finding forward-looking insights
In the past, people analyzed data to understand what had happened. But by using Big Data and AI, it is now possible to make predictions in the future and understand what will happen. Now, using predictive analytics, AI is driving Big Data decisions to make predictive analytics in more granular ways. Big data decisions have historically focused on existing and historical data points, typically yielding a linear ROI.

Big data and AI can help businesses increase productivity and reduce labor-intensive tasks.
With Big Data providing large volumes of data, artificial intelligence algorithms can reproduce certain behaviors in machines or in computer programs that were not feasible in the past. Data analysis becomes less labor intensive with the use of AI and Machine Learning. This technology helps organizations to analyze their data more efficiently and easily than what their employees usually do. But it is important to understand that AIs do not make conclusions like humans, but they learn by trial and error, and as a consequence Big Data is needed to improve the accuracy and precision of their data analysis.

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