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With modern-day work largely centered on digital platforms, automating the handling of big data has become more important than ever. This is where Artificial Intelligence (AI) comes in— performing tasks more efficiently by imitating our abilities to learn and solve problems. As technology advances at breakneck speed, fueled by the IoT environment, it has paved the way for a synergistic relationship between Artificial Intelligence and Big Data.
Thanks to AI, multiple ways to get insights have emerged into the market. AI has become the next step to query/SQL— methods used to analyze data initially. What used to be a statistical model has now converged with computer science and has become AI and Machine learning (ML). For instance, though employees still play an essential role in data management and analytics, it is the tools like AI and ML that assist a company in analyzing data more quickly and efficiently.
Now which businessperson wouldn’t like better efficiency, lower costs and slighter risks in his/ her business operations? Many business leaders and investors universally agree that AI and Machine Learning could help streamline operations, accelerate growth and fuel innovation. Companies today have realized this, and are rapidly deploying AI-related technologies.
Recently, Mathias Golombek, CTO at Exasol, told EnterprisesProject,
"AI is enhancing this analytics world with totally new capabilities to take semi-automatic decisions based on training data. It revolutionized the way you get rules, decisions, and predictions are done without complex human know-how."
Thus, it is safe to assume that with the help of AI, Big Data has grown to epic and exponential proportions.
Prescriptive analytics, leveraging AI, has the potential to provide company-wide, strategic insights helping the businesses to advance.
The data is still the data, but the ways of getting insights on it will improve, just as the combination of AI and big data is beginning to reveal its possibilities.