Predictive analytics for dummies

by Anasse Bari, Ph.D., Mohamed Chaouchi, and Tommy Jung

Business today relies on effectively using data to predict trends and sales. Predictive analytics is the tool that can make it happen, and this book eliminates the tricks and shows you how to use it. You'll learn to prepare and process your data, create goals, build a predictive model, get your organization's stakeholders on board and more

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Year of publication:	[2017] ; 2nd edition
Authors:	Bari, Anasse ; Chaouchi, Mohamed ; Jung, Tommy
Publisher:	Hoboken, NJ : Wiley
Subject:	Datenerhebung \| Data collection \| Big Data \| Big data \| Prognoseverfahren \| Forecasting model \| Visualisierung \| Visualization \| Datenmanagement \| Datenanalyse \| Data Mining
Description of contents:	Table of Contents [gbv.de]

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Extent:	viii, 443 Seiten Illustrationen
Series:	Learning made easy A Wiley Brand ... for dummies
Type of publication:	Book / Working Paper
Language:	English
Notes:	Titelzusätze auf dem Buchdeckel: Real-world tips for creating business value ; details on modeling, data clustering, and more ; enterprise use cases to help you get started Introduction. -- pt. 1. Getting started with predictive analytics. Entering the arena ; Predictive analytics in the wild ; Exploring your data types and associated techniques ; Complexities of data -- pt. 2. Incorporating algorithms in your models. Applying models ; Identifying similarities in data ; Predicting the future using data classification -- pt. 3. Developing a roadmap. Convincing your management to adopt predictive analytics ; Preparing data ; Building a predictive model ; Visualization of analytical results -- pt. 4. Programming predictive analytics. Creating basic prediction examples ; Creating basic examples of unsupervised predictions ; Predictive modeling with R ; Avoiding analysis traps ; -- pt. 5. Targeting big data Getting ready for enterprise analytics pt. 6 The part of tens. Ten reasons to implement predictive analytics ; Ten steps to build a predictive analytic model.
ISBN:	978-1-119-26700-3 ; 978-1-119-26701-0 ; 978-1-119-26702-7
Classification:	Mathematische Statistik
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012222667