Types of Problem Suited to Big Data Analysis(3)

 Bilal Hussain Malik

                                      Types of Problem Suited to Big Data Analysis


                                                       Unstructured Data Extraction

In the internet era, businesses are increasingly depending on big data solutions to extract value hidden in unstructured data - documents, images, audio, and video files that make up roughly 80% of all enterprise data. Social media sites and customer review forums have become goldmines for brand perception analysis, with natural language processing (NLP) algorithms trawling millions of tweets, posts, and comments to extract emerging trends, customer sentiment, and nascent PR crises. So, for instance, when a new smartphone model is launched, manufacturers can monitor social media in real time to catch and react to general griping about battery life or performance.

The healthcare industry has seen transformative advancements with the use of unstructured data analysis. Medical imaging AI systems can analyze thousands of MRI or CT scans in the time it takes a radiologist to review a single case, with some systems demonstrating higher accuracy at identifying stage-one tumors. Google's DeepMind made headlines when its AI system reduced the diagnosis time for certain eye diseases by an astonishing 94%, effectively saving countless patients from going blind by treating them earlier.

They are being powered by two pillars of technology: Natural Language Processing capable of understanding context, sentiment, and meaning in the human language, and Computer Vision systems capable of understanding visual data with superhuman precision. From Tesla's autonomous vehicles making sense of complex road situations to quality inspection systems in manufacturing identifying microscopic defects, the ability to extract intelligence from unstructured data is transforming every sector of the global economy and opening up new frontiers in artificial intelligence solutions.

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