000			03304nam a22003137a 4500
003			OSt
005			20260723100046.0
008			260723b |||||||| |||| 00| 0 eng d
020			_a9781836831082 [hardbound]
040			_aUniversity of Cebu-Banilad _cUniversity of Cebu-Banilad
100			_aSnow, Daphne, _eauthor.
245			_aBig data analytics : _btools and technology / _cby Daphne Snow.
250			_aFirst edition.
260			_aLondon, United Kingdom : _bVintage Press LTD., _cc2025.
300			_aix, 280 pages : _bcolor illustrations ; _c24 cm.
336			_2rdacontent _atext
337			_2rdamedia _aunmidiated
338			_2rdacarrier _avolume
504			_aIncludes bibliographical references and index.
505			_aContents : 1. Introduction to big data -- 2. Big data storage and processing frameworks -- 3. Data collection and data sources -- 4. Data preprocessing and cleaning -- 5. Data analysis and mining techniques -- 6. Machine learning for big data analytics -- 7. Big data visualization techniques -- 8. Data security and privacy in big data -- 9. Big data tools and technologies -- 10. Cloud computing for big data.
520			_a"In the rapidly evolving world of data science, Big Data analytics has become an essential discipline for organizations seeking to unlock the potential of vast amounts of information. As we move deeper into the digital age, the volume, velocity, and variety of data continue to grow exponentially. The ability to harness and interpret this data is no longer a luxury-it is a necessity. This book delves into the tools and technologies that have emerged as central to Big Data analytics, providing a comprehensive exploration of the systems that power modern data-driven decision-making In my experience, understanding the full scope of Big Data analytics requires not just familiarity with the underlying technologies but also insight into how they interconnect. From data storage and processing frameworks to the advanced analytics platforms that help extract value from data, the ecosystem is both complex and dynamic. This complexity is compounded by the need for scalability, flexibility, and real-time capabilities, which are all critical in today's fast-paced environments. Throughout the chapters, I aim to provide a clear understanding of the tools-ranging from Hadoop and Spark to newer innovations like machine learning algorithms and cloud-based solutions that are transforming industries. The integration of these technologies allows businesses to move from traditional data management to a more proactive, insight-driven approach. The goal of this book is not only to introduce readers to the landscape of Big Data tools and technologies but also to provide practical insights into how they can be applied to real-world challenges. It's a journey that blends theory with hands-on knowledge, offering a comprehensive guide to navigating the increasingly intricate world of Big Data analytics. —Daphne Snow" --Preface
521			_aAdult
541			_aPurchased _xOrtega, Eric _yCollege of Computer Studies _zComputer Science
546			_aText in English
650			_aBig data analytics.
942			_2ddc _cBK
998			_cJanna [new] _d07/23/2026
999			_c15566 _d15566