Autor/Autorin: Naikodi Chandrakant
Dr. Chandrakant Naikodi is presently working as an Associate Professor at Davanagere University, Davanagere. Before this position, he has 15 years of research and teaching experience. He is the author of Twenty Five Technical/Non- Technical books and published more than 100 technical papers in International Conferences/Journals.
Big data analytics can be defined as a process of examining large and varied data sets. We use advanced analytics techniques against the large data to uncover the hidden patterns, unknown correlations, market trends, customer preferences, and other useful information. This helps the organizations to make informed decisions.Analytics is an encompassing and multidimensional field. It uses mathematics, statistics, predictive modeling and machine-learning techniques to find meaningful patterns and knowledge in recorded data.
Naikodi, ChandrakantDr. Chandrakant Naikodi is presently working as an Associate Professor at Davanagere University, Davanagere. Before this position, he has 15 years of research and teaching experience. He is the author of Twenty Five Technical/Non- Technical books and published more than 100 technical papers in International Conferences/Journals.
Über den Autor
Il Dr. Chandrakant Naikodi lavora attualmente come Principal Applications Engineer in una multinazionale e ha conseguito i titoli DCE, B.E, M.E. e Ph.D in Computer Science and Engg. Il Dr. Suresh L lavora attualmente come direttore del CiTech di Bangalore e vanta oltre 24 anni di esperienza nell'insegnamento e nell'amministrazione. Ha pubblicato più di 100 pubblicazioni internazionali.
Klappentext
Big data analytics can be defined as a process of examining large and varied data sets. We use advanced analytics techniques against the large data to uncover the hidden patterns, unknown correlations, market trends, customer preferences, and other useful information. This helps the organizations to make informed decisions.Analytics is an encompassing and multidimensional field. It uses mathematics, statistics, predictive modeling and machine-learning techniques to find meaningful patterns and knowledge in recorded data.
