Jinho Kim – författare

Why Everyone Needs Analytical Skills Welcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)--your world is awash with data. As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your "quantitative literacy" guide--helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value. In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making.You'll gain crucial skills, including: * How to formulate a hypothesis * How to gather and analyze relevant data * How to interpret and communicate analytical results * How to develop habits of quantitative thinking * How to deal effectively with the "quants" in your organization Big data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don't have a business degree or if you aren't comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge--and gain a significant competitive edge.

Why Everyone Needs Analytical SkillsWelcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data.As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your “quantitative literacy" guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value.In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making. You’ll gain crucial skills, including:• How to formulate a hypothesis• How to gather and analyze relevant data• How to interpret and communicate analytical results• How to develop habits of quantitative thinking• How to deal effectively with the “quants” in your organizationBig data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don’t have a business degree or if you aren’t comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge—and gain a significant competitive edge.

The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics.

This book constitutes the workshop proceedings of the 21st International Conference on Database Systems for Advanced Applications, DASFAA 2016, held in Dallas, TX, USA, in April 2016.The volume contains 32 full papers (selected from 43 submissions) from 4 workshops, each focusing on a specific area that contributes to the main themes of DASFAA 2016: The Third International Workshop on Semantic Computing and Personalization, SeCoP 2016; the Third International Workshop on Big Data Management and Service, BDMS 2016; the First International Workshop on Big Data Quality Management, BDQM 2016; and the Second International Workshop on Mobile of Internet, MoI 2016.

This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.

This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017.

The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.

This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.

This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017.

The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.

This book will introduce the history and practices of mathematics education in Korea. How it has been influenced from Japan, America, and other countries, and has developed into the unique Korean style of mathematics education. The editors have planned to include most of the topics researchers outside Korea want to know mathematics education in Korea.