Bharath Mittapally

With an impressive track record spanning over half a decade, Bharath Kumar Mittapally has established himself as a seasoned data science consultant, positioning him at the forefront of the field. As a trusted data science consultant, he has worked with Fortune 500 companies such as Verizon and AT&T. Leveraging their vast datasets, he has adeptly employed cutting-edge data science and advanced machine learning techniques to combat fraudulent activities. Beyond fraud prevention, Bharath also worked with prominent companies like Xandr and Microsoft as a Data Scientist, working with their advertisement research department. Driven by his passion for continuous learning, he loves to engage with white papers, reviews, and research to remain abreast of the latest advancements and emerging trends in the field. His industry prowess led to his appointment as an IT Industry Expert and Judge for the Globee International Awards. He can be reached at [email protected].

Artificial Intelligence and Predictive Analytics for Business Growth

AI / Predictive Analytics / By

Introduction The journey from raw events to strategic decision-making encapsulates a transformative process in business. It begins with events – discrete occurrences in the business environment. These events generate data, the raw, unprocessed facts that are the lifeblood of any modern enterprise. As we collate and analyze this data, it transforms into information, providing insights […]

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Harmonizing HR Analytics: Addressing Legislative, Regulatory, Data Privacy Requirements, and Fraud Prevention

Technology Trends / Disrupters / Industry Insights, AI / Predictive Analytics / By

Introduction In today’s data-driven world, HR analytics has emerged as a powerful tool for organizations to gain insights and make informed decisions about their workforce. However, as organizations harness the potential of HR analytics, they must also navigate a complex landscape of legislative, regulatory, and data privacy requirements. Companies must address the ever-present threat of

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