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Getting Started with Business Analytics

for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data;

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Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and;

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Integration Challenges for Analytics, Business Intelligence, and Data Mining

information that is crucial for the success of the company. Without the integration of data (both structured and unstructured) mining in business;

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Data Analytics

This book has lots of valuable eye-opening information about data analytics, which will help you understand the concept of data mining;

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Data Science

, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing;

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Data Mining For Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications with JMP Pro(R) presents an applied and interactive approach to;

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Customer And Business Analytics

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying;

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Customer and Business Analytics

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying;

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Data Mining for Business Analytics

Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts;

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Big Data, Mining, and Analytics

approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining. Includes a foreword by Thomas H. Davenport;

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Big Data, Mining, and Analytics

approaches for decision making, including dashboards, OLAP cubes, data mining, and text mining. Includes a foreword by Thomas H. Davenport;

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Data Mining and Business Analytics with R

and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and;

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Decision Trees for Business Intelligence and Data Mining

This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business;

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Predictive Analytics, Data Mining and Big Data

Predictive analytics, data mining and big data are key topics for organizations who want to leverage the ever increasing amounts;

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Rapidminer

Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge continues in today's world, the need to master data mining, predictive;

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Business Analytics, Volume I

decision making approach that uses statistical and quantitative analysis along with data mining, management science, and fact-based data to measure;

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Predictive Analytics and Data Mining

and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its;

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Data Analytics

mining, data collection, big data analytics for business and business intelligence concepts.With this book, not only will you;

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Big Data, Data Mining, And Machine Learning

process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and;

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Business Intelligence and Analytics

Data is raw facts and figures and information is meaningful data that would be helpful for a person or company. Business intelligence;

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R for Business Analytics

metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from;

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Business Intelligence and Data Warehousing

Business Intelligence and Data Warehousing deals with the main components of a data warehouse for business intelligence applications;

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Recent Developments in Data Science and Business Analytics

processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization;

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Educational Improvement Through Data Mining & Analytics

data mining) are starting to be applied in education. The book examines the challenges being encountered and the potential of such efforts for;

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Trends and Applications in Knowledge Discovery and Data Mining

Techniques, BDM; Machine Learning for Sensory Data Analysis, MLSDA; Predictive Analytics for Critical Care, PACC; as well as Data Mining in Business;

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Computational Intelligence in Communications and Business Analytics

); computational intelligence; data science and advanced data analytics; and intelligent data mining and data warehousing.;

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Trends and Applications in Knowledge Discovery and Data Mining

selected from 179 submissions. The workshops affiliated with PAKDD 2014 include: Data Analytics for Targeted Healthcare, DANTH; Data Mining and;

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