Preface

15

Target Audience

15

How to Read this Book

16

What You Can Expect from This Book

16

How This Book Is Organized

17

Acknowledgments

19

Conclusion

19

1 Introduction

21

1.1 Performance and Its Relation to User Experience

22

1.1.1 Why the Design Phase Is Important

22

1.1.2 Who Manages Performance?

24

1.1.3 Validating Dashboards for Performance

26

1.2 SAP Analytics Cloud Performance

30

1.2.1 Why Performance Matters

30

1.2.2 Common Performance Issues

33

1.2.3 Understanding the Software Architecture

36

1.2.4 On-premise versus Cloud: General Limitations

38

1.3 Summary

42

2 Measuring, Testing, and Monitoring Performance

45

2.1 Different Types of Performance Tests

46

2.1.1 Performance Test Types

46

2.1.2 Performance Test Layers

50

2.1.3 Performance Test Tools

51

2.2 Performance Testing versus Performance Engineering

52

2.2.1 Performance Testing

53

2.2.2 Performance Engineering

53

2.3 Performance Testing Process

55

2.4 Defining the Metrics to Measure

58

2.4.1 Metrics that Measure Time

58

2.4.2 Metrics that Measure System Key Performance Indicators

61

2.4.3 Metrics that Measure Dashboard-specific Key Performance Indicators

62

2.5 Setting Performance Goals

64

2.5.1 Performance Goals for Different Test Types

65

2.5.2 Performance Goals for Different Metrics

66

2.6 Measuring Performance and System Key Performance Indicators

67

2.6.1 Measuring Performance Using Chrome DevTools

68

2.6.2 Measuring Network Traffic Using Chrome DevTools

72

2.6.3 Measuring Memory Consumption Using Chrome DevTools

73

2.6.4 Measuring CPU Consumption

74

2.6.5 Measuring Network Bandwidth

76

2.6.6 Measuring Dashboard Performance Using Onboard Analysis Tools

78

2.7 Creating Benchmark Tests

79

2.7.1 Prerequisites of a Benchmark Test

79

2.7.2 Phases of a Benchmark Test

80

2.8 SAP Analytics Cloud Performance Equation

81

2.9 Ten Golden Rules for Efficient SAP Analytics Cloud Dashboards

83

2.10 Summary

89

3 Optimizing Performance in the Story Builder

91

3.1 General Settings to Improve Performance

92

3.1.1 Using Multiple Models in a Story

92

3.1.2 Query Merging

93

3.1.3 Optimize Story Building Performance

94

3.1.4 Re-save the Story

95

3.1.5 Optimized View Mode

95

3.1.6 Performance Warning Notification

99

3.1.7 Progressive Chart Rendering

100

3.2 Optimizing the Story Design

100

3.2.1 Story Structure

101

3.2.2 Charts

107

3.2.3 Tables

111

3.2.4 Images

117

3.3 Optimizing Filters, Calculations, and Linked Analysis

118

3.3.1 Filtering and Drilling

118

3.3.2 Calculations and Restricted Measures

122

3.4 Optimizing Mobile Device Performance

124

3.4.1 Device and App Settings

124

3.4.2 Optimized iOS and View Time Optimization

125

3.4.3 Rethink the Design on Mobile Devices

126

3.5 Using the Explorer View to Improve Performance

128

3.5.1 Accessing the Explorer View

128

3.5.2 Deactivate Auto-Synchronization

129

3.5.3 Show Only Required Dimensions and Measures

130

3.6 Planning Scenarios: Optimizing Settings and Advanced Formulas

131

3.6.1 Version Management

131

3.6.2 Data Entry

132

3.6.3 Data Actions, Multi Actions, and Allocations

134

3.6.4 Optimize Advanced Formulas

136

3.7 The Performance Analysis Tool

147

3.7.1 Accessing the Performance Analysis Tool

148

3.7.2 Using the Performance Analysis Tool

150

3.7.3 Optimizing Your System with the Results

157

3.8 Best Practices

159

3.9 Summary

161

4 Analytics Designer Performance

163

4.1 Avoiding Poor Performance When Creating an Analytics Application

163

4.1.1 The Issue of Poor Performance in the Edit Mode

164

4.1.2 Split Up Your Dashboard into Smaller Analytics Applications

165

4.1.3 Leverage the Copy and Paste Functionality

166

4.1.4 Test Before Implementing Large Changes

167

4.2 General Rules to Improve Performance

168

4.2.1 Remember Chapter Three

168

4.2.2 Don’t Reinvent the Wheel or Overcomplicate Things

169

4.2.3 Limit the Number of Widgets

171

4.3 Optimizing the Application Structure

172

4.3.1 How Is an Analytics Application Loaded?

172

4.3.2 Leveraging the Load Invisible Widgets in Background Setting

174

4.3.3 Avoid Executing a Script in the OnInitialization Event

176

4.3.4 Pause the Refresh of Data to Reduce Loading Times

177

4.3.5 Split Up Content to Distribute Loading Times and Limit What Is Shown at Startup

178

4.4 Optimizing Responsive Design Performance for Mobile and Other Devices

184

4.4.1 Leverage Built-in Functionalities Instead of Scripting Everything

185

4.4.2 Avoid Resizing Unnecessarily

187

4.5 Optimizing Performance for Scripts

190

4.5.1 Basic Scripting Best Practices

191

4.5.2 Do’s and Don’ts of Scripting

192

4.5.3 Tools and Settings to Leverage in Your Scripts

193

4.6 Analytics Application Script Performance Popup Tool

195

4.6.1 What Is the Script Performance Popup Tool?

196

4.6.2 First Example: Measuring Specific Parts of Complex Scripting

197

4.6.3 Second Example: Viewing Bottlenecks Where Scripting Must Wait for Widgets to Load

198

4.7 Best Practices

199

4.8 Summary

200

5 Modeler Performance

203

5.1 General Modeler Settings to Improve Performance

203

5.1.1 Number of Data Sources

203

5.1.2 Show Unbooked Data in a Chart

204

5.1.3 Avoid Specifying Exception Aggregations

205

5.2 Choosing an Efficient Model

207

5.2.1 The Data Source Type

207

5.2.2 The Model Type

209

5.2.3 Datasphere Model

210

5.3 Performance of Acquired Models and Live Connection Models

211

5.4 Optimizing Performance for Planning Models

211

5.4.1 Delete Private Versions

212

5.4.2 Limit Public Version Data in Edit Mode

213

5.4.3 Filtering during the Modeling Process

214

5.4.4 Data Entry

214

5.5 Best Practices

214

5.6 Summary

215

6 Optimizing Backend and Tenant Settings

217

6.1 Optimizing Backend Data Storage Connection

217

6.1.1 Reduce Data as Early as Possible

218

6.1.2 Delete Dimensions in the Model

219

6.1.3 Hide Dimensions in the Model Design

220

6.1.4 Do Calculations After Aggregation

221

6.1.5 Perform Calculations in the Backend

221

6.1.6 Write Scripts in a Way that Avoids Extra Calls Against the Backend

222

6.2 Optimizations in the Backend Data

222

6.3 System Configuration Settings to Improve Performance

224

6.3.1 Optimize Story Building Performance

224

6.3.2 Progressive Chart Rendering

224

6.3.3 Query Batching

226

6.3.4 Increase the Number of SAP Business Warehouse Parallel Queries

231

6.3.5 Reduce the Metadata Loading in Your Widget

232

6.4 Best Practices

234

6.5 Summary

235

7 Viewer Choices

237

7.1 Optimizations When Viewing Dashboards

237

7.1.1 Which Browser to Use

238

7.1.2 Network Issues

240

7.1.3 The Impact of Using a Virtual Private Network

242

7.1.4 Computer Resources

243

7.1.5 Older Computers

245

7.1.6 Interacting with the Dashboard

246

7.2 Optimizations When Presenting to Others

247

7.2.1 Preloading Dashboards

247

7.2.2 Screen Sharing

248

7.2.3 Use of a Wireless Projector in a Hybrid Meeting

249

7.3 Best Practices

250

7.4 Summary

251

8 Optimized Dashboard Using Acquired Data

253

8.1 Scenario

253

8.2 Data Structure

257

8.2.1 Data Source

257

8.2.2 Building a Model in SAP Analytics Cloud

262

8.3 Dashboard Features

264

8.4 Building an Efficient Dashboard

265

8.4.1 Building the Dashboard Page 1 (Metrics)

265

8.4.2 Building the Dashboard Page 2 (Comparison)

274

8.4.3 Building the Dashboard Page 3 (Theaters)

276

8.5 Summary

280

9 Optimized Dashboard Using Live Data Connection

281

9.1 Live Data Connection Scenarios

281

9.1.1 Advantages and Disadvantages of a Live Data Connection

282

9.1.2 Scenario 1

282

9.1.3 Scenario 2

283

9.2 Data Structure

284

9.2.1 Creation of an SAP Business Warehouse Connection

284

9.2.2 Creation of an SAP HANA Connection

286

9.2.3 Creation of a Model

287

9.2.4 Scenario 1: Data Structure of an SAP Business Warehouse Connection

289

9.2.5 Scenario 2: Data Structure of an SAP HANA Connection

290

9.3 Dashboard Features

292

9.3.1 Scenario 1: SAP Business Warehouse Connection

294

9.3.2 Scenario 2: SAP HANA Connection

299

9.3.3 Other Live Connection-specific Features

301

9.3.4 Live Connection Limitations

302

9.4 Guidelines for Building an Efficient Dashboard

303

9.5 Summary

304

10 Optimized Dashboard Using the Analytics Designer

305

10.1 Scenario

306

10.2 Data Structure

308

10.2.1 Data Source

308

10.2.2 Building a Model in SAP Analytics Cloud

310

10.3 Dashboard Features

314

10.4 Building an Efficient Dashboard

315

10.4.1 Building the Dashboard Foundation

315

10.4.2 Building the Dashboard Page 1 (Overview Page)

325

10.4.3 Building the Dashboard Page 2 (by Food/Drink Page)

328

10.5 Summary

331

Appendices

333

A Further Reading

333

A.1 Chapter 1: Introduction

333

A.2 Chapter 2: Measuring, Testing, and Monitoring Performance

333

A.3 Chapter 3: Story Builder Performance

334

A.4 Chapter 4: Analytics Designer Performance

334

A.5 Chapter 5: Modeler Performance

334

A.6 Chapter 6: Optimizing Backend and Tenant Settings

334

A.7 Chapter 7: Viewer Choices

334

B The Authors

337