SAP Analytics Cloud: Predictive Analytics by Antoine Chabert Hardcover Book

Description: SAP Analytics Cloud by Antoine Chabert, David Serre Todays organizations must be prepared for tomorrows events. Forecast future behavior in SAP Analytics Cloud with this comprehensive guide to predictive analytics! Automate your models and dive into the data science with this all-in-one guide! FORMAT Hardcover CONDITION Brand New Publisher Description Todays organizations must be prepared for tomorrows events. Forecast future behavior in SAP Analytics Cloud with this comprehensive guide to predictive analytics! Start by learning about the data types, scenarios, and methods used in predictive analytics projects. Then follow step-by-step instructions to build, analyze, and apply predictive models to your business data using classification, time series forecasting, and regression analysis. Automate your models and dive into the data science with this all-in-one guide!In this book, youll learn about:a. Predictive Scenarios and Projects Understand the basics of predictive analytics in SAP Analytics Cloud: scenarios, data types, and actions. Then plan your predictive project, including identifying the key stakeholders and reviewing the methodology. b. Build, Train, Analyze, and ApplyMaster predictive models from end to end. Create classification, time series, and regression models; then train them to identify business patterns. Analyze and apply the results of your models to data in SAP Analytics Cloud.c. Practical DemonstrationsSee predictive analytics in action! Identify use cases for predictive modeling. For each data model, understand practical applications through curated examples with sample business data.Highlights include:1) Predictive scenarios2) Predictive forecasts3) Data modeling4) Planning5) Time series model6) Classification model7) Regression model8) Multi-actions9) Data science10) Stories and dashboards Author Biography Antoine Chabert is a product manager for SAP Analytics Cloud. He joined SAP more than 16 years ago and developed his expertise in SAP Analytics products, including SAP BusinessObjects, SAP Lumira, SAP Predictive Analytics, and SAP Analytics Cloud, in various functional roles. He helps SAP Analytics Cloud customers get the most out of the product and he works with SAP Engineering to create exciting innovations, connecting predictive analytics, business intelligence, and planning. Antoine holds a masters degree in computer science engineering. Outside of the office, he loves reading, playing badminton, and spending time with his family. David Serre is the product owner of the smart predict capability in SAP Analytics Cloud. He works closely with the product management team to convert customer needs into the features delivered in smart predict. David holds a masters degree in computer science and data exploration. In 2007, he started working as a software developer and later became a product owner for KXEN, an editor of predictive solutions. David joined SAP in 2014 and has worked as product owner for predictive analytics and smart predict since then. Table of Contents ... Preface ... 15... Objective of This Book ... 15... Target Audience ... 16... Structure of This Book ... 16... Acknowledgments ... 18... Conclusion ... 19I ... Getting Started ... 211 ... An Introduction to Predictive Analytics in SAP Analytics Cloud ... 231.1 ... The Importance of Predictive Analytics ... 231.2 ... Predictive Analytics in SAP Analytics Cloud ... 261.3 ... Customer Use Cases ... 301.4 ... Summary ... 342 ... What Are Predictive Scenarios? ... 352.1 ... Introducing Predictive Scenarios ... 352.2 ... The Different Types of Predictive Scenarios ... 412.3 ... The Predictive Ecosystem ... 422.4 ... Summary ... 513 ... Predictive Analytics Projects ... 533.1 ... Predictive Analytics Project Stakeholders ... 533.2 ... How to Implement a Predictive Analytics Project ... 563.3 ... Summary ... 68II ... Time Series Forecasting Models ... 694 ... Introducing Time Series Forecasting Models ... 714.1 ... What Is Time Series Forecasting? ... 714.2 ... Data Sources for Time Series Forecasting Models ... 764.3 ... End-to-End Time Series Forecasting Workflows ... 824.4 ... Summary ... 845 ... Using Predictive Forecasts in the Planning Process ... 855.1 ... Business Scenario ... 855.2 ... Planning Models ... 865.3 ... Creating Time Series Forecasting Models with Predictive Planning ... 925.4 ... Understanding Time Series Forecasting Models ... 1085.5 ... Improving Time Series Forecasting Models with Predictive Planning ... 1205.6 ... Saving Predictive Forecasts ... 1245.7 ... Including Predictive Forecasts in a Story ... 1265.8 ... Summary ... 1326 ... Automating the Production of Predictive Forecasts ... 1336.1 ... Introducing Multi Actions ... 1336.2 ... Creating Predictive Steps in Multi Actions ... 1346.3 ... Using Multi Actions ... 1386.4 ... Summary ... 1427 ... Time Series Forecasting Models Using Datasets ... 1437.1 ... Business Scenario ... 1437.2 ... Creating and Editing Datasets ... 1447.3 ... Creating Time Series Forecasting Models on Datasets ... 1477.4 ... Understanding Time Series Forecasting Models Based on Datasets ... 1547.5 ... Improving Time Series Forecasting Models Based on Datasets ... 1577.6 ... Saving Predictive Forecasts ... 1587.7 ... Including Predictive Forecasts in a Story ... 1607.8 ... Summary ... 1678 ... Best Practices and Tips for Time Series Forecasting Models ... 1698.1 ... Going Beyond 1,000 Entities ... 1698.2 ... Handling Time Series with Missing Data ... 1738.3 ... Considering Time Granularities ... 1778.4 ... Creating Ad Hoc Performance Indicators ... 1808.5 ... Generating What-If Simulations ... 1828.6 ... Forecasting Data at the Right Level ... 1848.7 ... Summary ... 1869 ... The Data Science behind Time Series Forecasting Models ... 1879.1 ... End-to-End Process ... 1879.2 ... Additive Modeling Technique ... 1889.3 ... Exponential Smoothing ... 1949.4 ... Predictive Model Selection ... 1999.5 ... Summary ... 200III ... Classification Models and Regression Models ... 20110 ... Introducing Classification Models and Regression Models ... 20310.1 ... What Is Classification? ... 20310.2 ... What Is Regression? ... 20710.3 ... Data Sources for Classification Models and Regression Models ... 20910.4 ... End-to-End Workflow ... 21310.5 ... Summary ... 21411 ... Creating Classification Insights to Enrich Stories ... 21711.1 ... Business Scenario ... 21711.2 ... Using Datasets with Classification Models ... 21811.3 ... Creating Classification Models ... 22211.4 ... Understanding Classification Models ... 22811.5 ... Improving Classification Models ... 24511.6 ... Applying Classification Models ... 24811.7 ... Enriching Stories with Classification Insights ... 25111.8 ... Summary ... 26012 ... Creating Regression Insights to Enrich Stories ... 26112.1 ... Business Scenario ... 26112.2 ... Using Datasets with Regression Models ... 26212.3 ... Creating Regression Models ... 26612.4 ... Understanding Regression Models ... 27012.5 ... Improving Regression Models ... 27512.6 ... Applying Regression Models ... 27612.7 ... Enriching Stories with Regression Insights ... 27912.8 ... Summary ... 28513 ... The Data Science behind Classification Models and Regression Models ... 28713.1 ... Fitting a Predictive Function ... 28713.2 ... Prerequisites to Generating a Model ... 29013.3 ... Evaluating the Model Performance ... 29113.4 ... End-to-End Automated Modeling ... 29713.5 ... Generating Predictive Insights ... 30213.6 ... Summary ... 30514 ... Conclusion ... 30714.1 ... Lessons Learned ... 30714.2 ... The Future of Predictive Scenarios in SAP Analytics Cloud ... 30714.3 ... Your Next Steps ... 308... The Authors ... 309... Index ... 311 Details ISBN1493224786 Author David Serre Publisher SAP Press Year 2024 ISBN-13 9781493224784 Format Hardcover Imprint SAP Press Country of Publication United States Place of Publication Maryland Subtitle Predictive Analytics Audience Professional & Vocational DEWEY 004.6782 Publication Date 2024-05-31 US Release Date 2024-05-31 Pages 315 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:159922629;

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