Preface

13

Objective of This Book

13

Target Audience

14

Structure of This Book

14

Additional Resources

15

Acknowledgments

16

1 Introduction

17

1.1 What Is Analytics?

17

1.2 SAP’s Data and Analytics Strategy

19

1.2.1 Core Pillars of SAP’s Data and Analytics Strategy

19

1.2.2 Comparing Cloud-Based and On-Premise Solutions

21

1.2.3 How Does SAP Datasphere Fit In?

22

1.3 Overview of SAP Analytics Cloud

23

1.3.1 Functional Areas

24

1.3.2 User Interface and Core Functionality

27

1.4 Architecture

45

1.5 Standalone and Embedded Versions of SAP Analytics Cloud

46

1.6 Summary

48

2 Data Integration

49

2.1 Data Sources Supported by SAP Analytics Cloud

49

2.1.1 Data Sources for Live Connections

49

2.1.2 Data Sources for Import Connections

55

2.2 Connection Types

61

2.2.1 Live Connections

61

2.2.2 Import Connections

66

2.2.3 Choosing a Connection Type

69

2.3 Integration Scenarios for Live Connections

70

2.3.1 Direct Connections via Cross-Origin Resource Sharing

70

2.3.2 Connections via Tunnels

75

2.3.3 Connections via Reverse Proxies

77

2.4 Integration Scenarios for Import Connections

79

2.4.1 Connections to On-Premise Data Sources

79

2.4.2 Import Connections to Cloud Data Sources

81

2.5 Summary

83

3 Navigation and Administration

85

3.1 Navigating the Home Screen and Main Menu

85

3.2 First Steps for Administrators

89

3.2.1 Users and Single Sign-On

89

3.2.2 Data Sources and Structures

91

3.2.3 Operational Concept

92

3.2.4 System Landscape

92

3.3 Administration Tools

96

3.3.1 Security

97

3.3.2 Transport

106

3.3.3 System

109

3.3.4 Administration

111

3.3.5 Files and Folder Structure

115

3.3.6 Content Network

118

3.3.7 Workspace Management

119

3.4 Creating Connections

120

3.5 Summary

123

4 Data Modeling

125

4.1 Why Use Data Models?

126

4.2 Types of Data Models

129

4.2.1 Datasets

129

4.2.2 Analytical Models

132

4.2.3 Planning Models

134

4.2.4 Embedded Models

135

4.3 Creating Models by Importing Data

135

4.3.1 Creating a Model

136

4.3.2 Creating Expressions

142

4.3.3 Executing Transformations

143

4.3.4 Creating Hierarchies

147

4.3.5 Creating Versions

148

4.4 Creating Models from Live Data Sources

150

4.5 Editing Models in the Modeler

158

4.5.1 Areas of the Modeler

160

4.5.2 Editing Models

163

4.6 Summary

169

5 Business Intelligence: Visualizations and Dashboards

171

5.1 What Are Stories?

172

5.2 Creating Stories

174

5.2.1 Pages

175

5.2.2 Classic Data Exploration and Your First Charts

178

5.2.3 Launch a New Story

183

5.2.4 Story Interface

184

5.3 Creating, Editing, and Formatting Charts

189

5.3.1 Creating a New Chart

189

5.3.2 Adding More Charts

195

5.3.3 Conditional Formatting

196

5.3.4 Showing Variances

197

5.3.5 Other Chart Functionalities

200

5.3.6 Defining Colors

205

5.3.7 Formatting Charts

206

5.3.8 Hierarchies

209

5.4 Creating, Editing, and Formatting Tables

209

5.5 Geo Maps

215

5.6 Texts, RSS Readers, and Other Elements

218

5.7 How Viewers Interact with Stories

221

5.7.1 Filters

222

5.7.2 Dimension and Measure Input Controls

230

5.7.3 Chart Interactions

232

5.8 Calculations

236

5.8.1 Calculated Accounts

237

5.8.2 Calculated Dimensions

240

5.9 Story Design

242

5.10 Sharing and Publishing Stories

245

5.10.1 Sharing, Exporting, and Publishing Stories

245

5.10.2 Publishing to Mobile Devices

249

5.11 Additional Story Functionalities

254

5.11.1 Creating an Embedded Model within a Story

254

5.11.2 Story Templates

255

5.11.3 Blending

255

5.11.4 Comments

258

5.11.5 Bookmarks

259

5.12 Optimized Story View Mode

259

5.13 Summary

261

6 Planning

263

6.1 Planning in SAP Analytics Cloud

263

6.1.1 Data Entry and Version Management

264

6.1.2 Planning within Stories

266

6.1.3 Planning Tools

268

6.2 Creating and Setting Up a Planning Model

270

6.2.1 Creating a Currency Conversion Table

271

6.2.2 Creating a Master Data Model

273

6.2.3 Uploading Transactional Data to the Model

281

6.2.4 Setting Up a Planning Model

286

6.3 Planning-Specific Functionality

289

6.3.1 Versions and Data Entry

289

6.3.2 Distributing Values

292

6.3.3 Allocations

297

6.3.4 Grid Pages

302

6.3.5 Value Driver Tree

305

6.3.6 Data Actions

309

6.3.7 Calendar

311

6.4 Summary

314

7 Predictive Analytics

317

7.1 What Is Predictive Analytics?

317

7.2 Smart Assist

322

7.2.1 Smart Discovery

322

7.2.2 Smart Insights

326

7.2.3 Search to Insight

328

7.2.4 R Visualizations

329

7.2.5 Automatic Forecasts for Time Series

333

7.2.6 Smart Grouping

335

7.3 Smart Predict: Predictive Scenarios

336

7.3.1 Time Series

336

7.3.2 Regressions and Classifications

343

7.4 Summary

343

8 Advanced Development Environment

345

8.1 The History of Stories and Applications

345

8.2 Creating Applications

348

8.2.1 Development Environment

349

8.2.2 Creating New Application Elements

352

8.3 Custom Widgets

366

8.4 Summary

370

9 SAP Digital Boardroom

373

9.1 What Is SAP Digital Boardroom?

374

9.2 Creating Boardrooms

379

9.2.1 Boardroom Types

379

9.2.2 Using Charts in a Boardroom

381

9.2.3 Creating an Agenda

382

9.2.4 Creating a Dashboard

387

9.3 Hardware Recommendations

392

9.4 Summary

393

10 SAP Analytics Hub and the Analytics Catalog for SAP Analytics Cloud

395

10.1 What Is SAP Analytics Hub?

396

10.2 Setup and Content Creation

398

10.2.1 SAP Analytics Hub Cockpit

399

10.2.2 Edit Mode and Content Management

404

10.3 Analytics Catalog

406

10.3.1 Adding Content to the Analytics Catalog

406

10.3.2 Browsing the Analytics Catalog

408

10.4 Summary

409