Predictive Analytics For Dummies (For Dummies Series) - Softcover

Bari, Dr. Anasse; Chaouchi, Mohamed; Jung, Tommy

Softcover

ISBN 10: 1118728963 ISBN 13: 9781118728963

Publisher: John Wiley & Sons, 2014

Synopsis

Combine business sense, statistics, and computers in a new and intuitive way, thanks to Big Data

Predictive analytics is a branch of data mining that helps predict probabilities and trends. Predictive Analytics For Dummies explores the power of predictive analytics and how you can use it to make valuable predictions for your business, or in fields such as advertising, fraud detection, politics, and others. This practical book does not bog you down with loads of mathematical or scientific theory, but instead helps you quickly see how to use the right algorithms and tools to collect and analyze data and apply it to make predictions.

Topics include using structured and unstructured data, building models, creating a predictive analysis roadmap, setting realistic goals, budgeting, and much more.

• Shows readers how to use Big Data and data mining to discover patterns and make predictions for tech–savvy businesses
• Helps readers see how to shepherd predictive analytics projects through their companies
• Explains just enough of the science and math, but also focuses on practical issues such as protecting project budgets, making good presentations, and more
• Covers nuts–and–bolts topics including predictive analytics basics, using structured and unstructured data, data mining, and algorithms and techniques for analyzing data
• Also covers clustering, association, and statistical models; creating a predictive analytics roadmap; and applying predictions to the web, marketing, finance, health care, and elsewhere

Propose, produce, and protect predictive analytics projects through your company with Predictive Analytics For Dummies.

About this title

About the Author

Dr. Anasse Bari is a Fulbright scholar, a software engineer, and a data mining expert. Mohamed Chaouchi has conducted extensive research using data mining methods in both health and financial domains. Tommy Jung has worked extensively on natural language processing and algorithmic trading using machine learning.

From the Back Cover

Learn to:

• Analyze structured and unstructured data
• Use algorithms and data analysis techniques
• Build clustering, classification and statistical models
• Apply predictive analytics to your website and marketing efforts

A practical guide to using Big Data and technology to discover real–world insights

Predict the future! Data is growing exponentially and predictive analytics is your organization s key to making use of it to create a competitive advantage. This comprehensive resource will help you define real–world projects and takes a step–by–step approach to the technical aspects of predictive analytics so you can get up and running right away.

• Enter the arena jump into predictive analytics by discovering how data can translate to a competitive advantage
• Incorporating algorithms discover data models, how to identify similarities and relationships, and how to predict the future through data classification
• Developing a roadmap prepare your data, create goals, structure and process your data, and build a predictive model that will get stakeholder buy–in
• Programming predictive analytics use in–depth tips to install software, modules, and libraries to get going with prediction models
• Making predictive analytics work gain an understanding of the typical pushback on predictive analytics adoption and how to overcome it

Open the book and find:

• Real–world tips for creating business value
• Common use cases to help you get started
• Details on modeling, k–means clustering, and more
• How you can predict the future with classification
• Information on structuring your data
• Methods for testing models
• Hands–on guides to software installation
• Tips on outlining business goals and approaches

Edition details

• Publisher: John Wiley & Sons
• Publication date: 2014
• Language: English
• ISBN 10: 1118728963
• ISBN 13: 9781118728963
• Binding: Paperback
• Edition number: 1
• Number of pages: 360