Welcome!

Oracle Authors: Pat Romanski, Yeshim Deniz, Michael Bushong, Avi Rosenthal

News Feed Item

Software: Global Industry Almanac, MarketLine

NEW YORK, Jan. 8, 2013 /PRNewswire/ -- Reportlinker.com announces that a new market research report is available in its catalogue:

Software: Global Industry Almanac, MarketLine

http://www.reportlinker.com/p01080569/Software-Global-Industry-Almanac-M...

Software: Global Industry Almanac is an essential resource for top-level data and analysis covering the Software industry. It includes detailed data on market size and segmentation, textual analysis of the key trends and competitive landscape, and profiles of the leading companies. This incisive report provides expert analysis on a global, regional and country basis.

Scope of the Report

* Contains an executive summary and data on value, volume and segmentation

* Provides textual analysis of the industry's prospects, competitive landscape and profiles of the leading companies

* Incorporates in-depth five forces competitive environment analysis and scorecards

* Covers the Global, European and Asia-Pacific markets as well as individual chapters on Australia, Belgium, Brazil, Canada, China, Czech Republic, Denmark, France, Germany, Hungary, India, Italy, Japan, Mexico, Netherlands, Norway, Poland, Russia, Singapore, South Africa, South Korea, Spain, Sweden, United Kingdom and United States.

* Includes a five-year forecast of the industry

Highlights

The global software market grew by 6.6% in 2011 to reach a value of $292.9 billion.

In 2016, the global software market is forecast to have a value of $396.7 billion, an increase of 35.4% since 2011.

General business productivity & home applications is the largest segment of the global software market, accounting for 24% of the market's total value.

Americas accounts for 42.6% of the global software market value.

Why you should buy this report

* Spot future trends and developments

* Inform your business decisions

* Add weight to presentations and marketing materials

* Save time carrying out entry-level research

Market Definition

The computer software market consists of systems and application software. Systems software comprises operating systems, network and database management, and other systems software. Application software comprises general business productivity and home use applications, cross-industry and vertical market applications, and other application software. Market value figures are assessed at manufacturer selling price (MSP), based on revenues from software sales and licenses. Any currency conversions used in the creation of this report have been calculated using constant 2011 annual average exchange rates.TABLE OF CONTENTSEXECUTIVE SUMMARY 2Market value 2Market value forecast 2Category segmentation 2Geography segmentation 2Introduction 32What is this report about? 32Who is the target reader? 32How to use this report 32Definitions 32Global Software 33Market Overview 33Market Data 34Market Segmentation 35Market outlook 37Five forces analysis 38Software in Asia-Pacific 44Market Overview 44Market Data 45Market Segmentation 46Market outlook 48Five forces analysis 49Software in Europe 55Market Overview 55Market Data 56Market Segmentation 57Market outlook 59Five forces analysis 60Software in France 66Market Overview 66Market Data 67Market Segmentation 68Market outlook 70Five forces analysis 71Macroeconomic indicators 77Software in Germany 79Market Overview 79Market Data 80Market Segmentation 81Market outlook 83Five forces analysis 84Macroeconomic indicators 90Software in Australia 92Market Overview 92Market Data 93Market Segmentation 94Market outlook 96Five forces analysis 97Macroeconomic indicators 103Software in Belgium 105Market Overview 105Market Data 106Market Segmentation 107Market outlook 109Five forces analysis 110Macroeconomic indicators 116Software in Brazil 118Market Overview 118Market Data 119Market Segmentation 120Market outlook 122Five forces analysis 123Macroeconomic indicators 129Software in Canada 131Market Overview 131Market Data 132Market Segmentation 133Market outlook 135Five forces analysis 136Macroeconomic indicators 142Software in China 144Market Overview 144Market Data 145Market Segmentation 146Market outlook 148Five forces analysis 149Macroeconomic indicators 155Software in The Czech Republic 157Market Overview 157Market Data 158Market Segmentation 159Market outlook 161Five forces analysis 162Macroeconomic indicators 168Software in Denmark 170Market Overview 170Market Data 171Market Segmentation 172Market outlook 174Five forces analysis 175Macroeconomic indicators 181Software in Hungary 183Market Overview 183Market Data 184Market Segmentation 185Market outlook 187Five forces analysis 188Macroeconomic indicators 194Software in India 196Market Overview 196Market Data 197Market Segmentation 198Market outlook 200Five forces analysis 201Macroeconomic indicators 207Software in Italy 209Market Overview 209Market Data 210Market Segmentation 211Market outlook 213Five forces analysis 214Macroeconomic indicators 220Software in Japan 222Market Overview 222Market Data 223Market Segmentation 224Market outlook 226Five forces analysis 227Macroeconomic indicators 233Software in Mexico 235Market Overview 235Market Data 236Market Segmentation 237Market outlook 239Five forces analysis 240Macroeconomic indicators 246Software in The Netherlands 248Market Overview 248Market Data 249Market Segmentation 250Market outlook 252Five forces analysis 253Macroeconomic indicators 259Software in Norway 261Market Overview 261Market Data 262Market Segmentation 263Market outlook 265Five forces analysis 266Macroeconomic indicators 272Software in Poland 274Market Overview 274Market Data 275Market Segmentation 276Market outlook 278Five forces analysis 279Macroeconomic indicators 285Software in Russia 287Market Overview 287Market Data 288Market Segmentation 289Market outlook 291Five forces analysis 292Macroeconomic indicators 298Software in Singapore 300Market Overview 300Market Data 301Market Segmentation 302Market outlook 304Five forces analysis 305Macroeconomic indicators 311Software in South Africa 313Market Overview 313Market Data 314Market Segmentation 315Market outlook 316Five forces analysis 317Macroeconomic indicators 323Software in South Korea 325Market Overview 325Market Data 326Market Segmentation 327Market outlook 329Five forces analysis 330Macroeconomic indicators 336Software in Spain 338Market Overview 338Market Data 339Market Segmentation 340Market outlook 342Five forces analysis 343Macroeconomic indicators 349Software in Sweden 351Market Overview 351Market Data 352Market Segmentation 353Market outlook 355Five forces analysis 356Macroeconomic indicators 362Software in The United Kingdom 364Market Overview 364Market Data 365Market Segmentation 366Market outlook 368Five forces analysis 369Macroeconomic indicators 375Software in The United States 377Market Overview 377Market Data 378Market Segmentation 379Market outlook 381Five forces analysis 382Macroeconomic indicators 388Company Profiles 390Leading companies 390Appendix 438Methodology 438

LIST OF TABLES

Table 1: Global software market value: $ billion, 2007–11 34

Table 2: Global software market category segmentation: $ billion, 2011 35

Table 3: Global software market geography segmentation: $ billion, 2011 36

Table 4: Global software market value forecast: $ billion, 2011–16 37

Table 5: Asia-Pacific software market value: $ billion, 2007–11 45

Table 6: Asia–Pacific software market category segmentation: $ billion, 2011 46

Table 7: Asia–Pacific software market geography segmentation: $ billion, 2011 47

Table 8: Asia-Pacific software market value forecast: $ billion, 2011–16 48

Table 9: Europe software market value: $ billion, 2007–11 56

Table 10: Europe software market category segmentation: $ billion, 2011 57

Table 11: Europe software market geography segmentation: $ billion, 2011 58

Table 12: Europe software market value forecast: $ billion, 2011–16 59

Table 13: France software market value: $ billion, 2007–11 67

Table 14: France software market category segmentation: $ billion, 2011 68

Table 15: France software market geography segmentation: $ billion, 2011 69

Table 16: France software market value forecast: $ billion, 2011–16 70

Table 17: France size of population (million), 2007–11 77

Table 18: France gdp (constant 2000 prices, $ billion), 2007–11 77

Table 19: France gdp (current prices, $ billion), 2007–11 77

Table 20: France inflation, 2007–11 78

Table 21: France consumer price index (absolute), 2007–11 78

Table 22: France exchange rate, 2007–11 78

Table 23: Germany software market value: $ billion, 2007–11 80

Table 24: Germany software market category segmentation: $ billion, 2011 81

Table 25: Germany software market geography segmentation: $ billion, 2011 82

Table 26: Germany software market value forecast: $ billion, 2011–16 83

Table 27: Germany size of population (million), 2007–11 90

Table 28: Germany gdp (constant 2000 prices, $ billion), 2007–11 90

Table 29: Germany gdp (current prices, $ billion), 2007–11 90

Table 30: Germany inflation, 2007–11 91

Table 31: Germany consumer price index (absolute), 2007–11 91

Table 32: Germany exchange rate, 2007–11 91

Table 33: Australia software market value: $ billion, 2007–11 93

Table 34: Australia software market category segmentation: $ billion, 2011 94

Table 35: Australia software market geography segmentation: $ billion, 2011 95

Table 36: Australia software market value forecast: $ billion, 2011–16 96

Table 37: Australia size of population (million), 2007–11 103

Table 38: Australia gdp (constant 2000 prices, $ billion), 2007–11 103

Table 39: Australia gdp (current prices, $ billion), 2007–11 103

Table 40: Australia inflation, 2007–11 104

Table 41: Australia consumer price index (absolute), 2007–11 104

Table 42: Australia exchange rate, 2007–11 104

Table 43: Belgium software market value: $ billion, 2007–11 106

Table 44: Belgium software market category segmentation: $ billion, 2011 107

Table 45: Belgium software market geography segmentation: $ billion, 2011 108

Table 46: Belgium software market value forecast: $ billion, 2011–16 109

Table 47: Belgium size of population (million), 2007–11 116

Table 48: Belgium gdp (constant 2000 prices, $ billion), 2007–11 116

Table 49: Belgium gdp (current prices, $ billion), 2007–11 116

Table 50: Belgium inflation, 2007–11 117

Table 51: Belgium consumer price index (absolute), 2007–11 117

Table 52: Belgium exchange rate, 2007–11 117

Table 53: Brazil software market value: $ billion, 2007–11 119

Table 54: Brazil software market category segmentation: $ billion, 2011 120

Table 55: Brazil software market geography segmentation: $ billion, 2011 121

Table 56: Brazil software market value forecast: $ billion, 2011–16 122

Table 57: Brazil size of population (million), 2007–11 129

Table 58: Brazil gdp (constant 2000 prices, $ billion), 2007–11 129

Table 59: Brazil gdp (current prices, $ billion), 2007–11 129

Table 60: Brazil inflation, 2007–11 130

Table 61: Brazil consumer price index (absolute), 2007–11 130

Table 62: Brazil exchange rate, 2007–11 130

Table 63: Canada software market value: $ billion, 2007–11 132

Table 64: Canada software market category segmentation: $ billion, 2011 133

Table 65: Canada software market geography segmentation: $ billion, 2011 134

Table 66: Canada software market value forecast: $ billion, 2011–16 135

Table 67: Canada size of population (million), 2007–11 142

Table 68: Canada gdp (constant 2000 prices, $ billion), 2007–11 142

Table 69: Canada gdp (current prices, $ billion), 2007–11 142

Table 70: Canada inflation, 2007–11 143

Table 71: Canada consumer price index (absolute), 2007–11 143

Table 72: Canada exchange rate, 2007–11 143

Table 73: China software market value: $ billion, 2007–11 145

Table 74: China software market category segmentation: $ billion, 2011 146

Table 75: China software market geography segmentation: $ billion, 2011 147

Table 76: China software market value forecast: $ billion, 2011–16 148

Table 77: China size of population (million), 2007–11 155

Table 78: China gdp (constant 2000 prices, $ billion), 2007–11 155

Table 79: China gdp (current prices, $ billion), 2007–11 155

Table 80: China inflation, 2007–11 156

Table 81: China consumer price index (absolute), 2007–11 156

Table 82: China exchange rate, 2007–11 156

Table 83: Czech Republic software market value: $ billion, 2007–11 158

Table 84: Czech Republic software market category segmentation: $ billion, 2011 159

Table 85: Czech Republic software market geography segmentation: $ billion, 2011 160

Table 86: Czech Republic software market value forecast: $ billion, 2011–16 161

Table 87: Czech Republic size of population (million), 2007–11 168

Table 88: Czech Republic gdp (constant 2000 prices, $ billion), 2007–11 168

Table 89: Czech Republic gdp (current prices, $ billion), 2007–11 168

Table 90: Czech Republic inflation, 2007–11 169

Table 91: Czech Republic consumer price index (absolute), 2007–11 169

Table 92: Czech Republic exchange rate, 2007–11 169

Table 93: Denmark software market value: $ billion, 2007–11 171

Table 94: Denmark software market category segmentation: $ billion, 2011 172

Table 95: Denmark software market geography segmentation: $ billion, 2011 173

Table 96: Denmark software market value forecast: $ billion, 2011–16 174

Table 97: Denmark size of population (million), 2007–11 181

Table 98: Denmark gdp (constant 2000 prices, $ billion), 2007–11 181

Table 99: Denmark gdp (current prices, $ billion), 2007–11 181

Table 100: Denmark inflation, 2007–11 182

Table 101: Denmark consumer price index (absolute), 2007–11 182

Table 102: Denmark exchange rate, 2007–11 182

Table 103: Hungary software market value: $ billion, 2007–11 184

Table 104: Hungary software market category segmentation: $ billion, 2011 185

Table 105: Hungary software market geography segmentation: $ billion, 2011 186

Table 106: Hungary software market value forecast: $ billion, 2011–16 187

Table 107: Hungary size of population (million), 2007–11 194

Table 108: Hungary gdp (constant 2000 prices, $ billion), 2007–11 194

Table 109: Hungary gdp (current prices, $ billion), 2007–11 194

Table 110: Hungary inflation, 2007–11 195

Table 111: Hungary consumer price index (absolute), 2007–11 195

Table 112: Hungary exchange rate, 2007–11 195

Table 113: India software market value: $ billion, 2007–11 197

Table 114: India software market category segmentation: $ billion, 2011 198

Table 115: India software market geography segmentation: $ billion, 2011 199

Table 116: India software market value forecast: $ billion, 2011–16 200

Table 117: India size of population (million), 2007–11 207

Table 118: India gdp (constant 2000 prices, $ billion), 2007–11 207

Table 119: India gdp (current prices, $ billion), 2007–11 207

Table 120: India inflation, 2007–11 208

Table 121: India consumer price index (absolute), 2007–11 208

Table 122: India exchange rate, 2007–11 208

Table 123: Italy software market value: $ billion, 2007–11 210

Table 124: Italy software market category segmentation: $ billion, 2011 211

Table 125: Italy software market geography segmentation: $ billion, 2011 212

Table 126: Italy software market value forecast: $ billion, 2011–16 213

Table 127: Italy size of population (million), 2007–11 220

Table 128: Italy gdp (constant 2000 prices, $ billion), 2007–11 220

Table 129: Italy gdp (current prices, $ billion), 2007–11 220

Table 130: Italy inflation, 2007–11 221

Table 131: Italy consumer price index (absolute), 2007–11 221

Table 132: Italy exchange rate, 2007–11 221

Table 133: Japan software market value: $ billion, 2007–11 223

Table 134: Japan software market category segmentation: $ billion, 2011 224

Table 135: Japan software market geography segmentation: $ billion, 2011 225

Table 136: Japan software market value forecast: $ billion, 2011–16 226

Table 137: Japan size of population (million), 2007–11 233

Table 138: Japan gdp (constant 2000 prices, $ billion), 2007–11 233

Table 139: Japan gdp (current prices, $ billion), 2007–11 233

Table 140: Japan inflation, 2007–11 234

Table 141: Japan consumer price index (absolute), 2007–11 234

Table 142: Japan exchange rate, 2007–11 234

Table 143: Mexico software market value: $ billion, 2007–11 236

Table 144: Mexico software market category segmentation: $ billion, 2011 237

Table 145: Mexico software market geography segmentation: $ billion, 2011 238

Table 146: Mexico software market value forecast: $ billion, 2011–16 239

Table 147: Mexico size of population (million), 2007–11 246

Table 148: Mexico gdp (constant 2000 prices, $ billion), 2007–11 246

Table 149: Mexico gdp (current prices, $ billion), 2007–11 246

Table 150: Mexico inflation, 2007–11 247

Table 151: Mexico consumer price index (absolute), 2007–11 247

Table 152: Mexico exchange rate, 2007–11 247

Table 153: Netherlands software market value: $ billion, 2007–11 249

Table 154: Netherlands software market category segmentation: $ billion, 2011 250

Table 155: Netherlands software market geography segmentation: $ billion, 2011 251

Table 156: Netherlands software market value forecast: $ billion, 2011–16 252

Table 157: Netherlands size of population (million), 2007–11 259

Table 158: Netherlands gdp (constant 2000 prices, $ billion), 2007–11 259

Table 159: Netherlands gdp (current prices, $ billion), 2007–11 259

Table 160: Netherlands inflation, 2007–11 260

Table 161: Netherlands consumer price index (absolute), 2007–11 260

Table 162: Netherlands exchange rate, 2007–11 260

Table 163: Norway software market value: $ billion, 2007–11 262

Table 164: Norway software market category segmentation: $ billion, 2011 263

Table 165: Norway software market geography segmentation: $ billion, 2011 264

Table 166: Norway software market value forecast: $ billion, 2011–16 265

Table 167: Norway size of population (million), 2007–11 272

Table 168: Norway gdp (constant 2000 prices, $ billion), 2007–11 272

Table 169: Norway gdp (current prices, $ billion), 2007–11 272

Table 170: Norway inflation, 2007–11 273

Table 171: Norway consumer price index (absolute), 2007–11 273

Table 172: Norway exchange rate, 2007–11 273

Table 173: Poland software market value: $ billion, 2007–11 275

Table 174: Poland software market category segmentation: $ billion, 2011 276

Table 175: Poland software market geography segmentation: $ billion, 2011 277

Table 176: Poland software market value forecast: $ billion, 2011–16 278

Table 177: Poland size of population (million), 2007–11 285

Table 178: Poland gdp (constant 2000 prices, $ billion), 2007–11 285

Table 179: Poland gdp (current prices, $ billion), 2007–11 285

Table 180: Poland inflation, 2007–11 286

Table 181: Poland consumer price index (absolute), 2007–11 286

Table 182: Poland exchange rate, 2007–11 286

Table 183: Russia software market value: $ billion, 2007–11 288

Table 184: Russia software market category segmentation: $ billion, 2011 289

Table 185: Russia software market geography segmentation: $ billion, 2011 290

Table 186: Russia software market value forecast: $ billion, 2011–16 291

Table 187: Russia size of population (million), 2007–11 298

Table 188: Russia gdp (constant 2000 prices, $ billion), 2007–11 298

Table 189: Russia gdp (current prices, $ billion), 2007–11 298

Table 190: Russia inflation, 2007–11 299

Table 191: Russia consumer price index (absolute), 2007–11 299

Table 192: Russia exchange rate, 2007–11 299

Table 193: Singapore software market value: $ billion, 2007–11 301

Table 194: Singapore software market category segmentation: $ billion, 2011 302

Table 195: Singapore software market geography segmentation: $ billion, 2011 303

Table 196: Singapore software market value forecast: $ billion, 2011–16 304

Table 197: Singapore size of population (million), 2007–11 311

Table 198: Singapore gdp (constant 2000 prices, $ billion), 2007–11 311

Table 199: Singapore gdp (current prices, $ billion), 2007–11 311

Table 200: Singapore inflation, 2007–11 312

Table 201: Singapore consumer price index (absolute), 2007–11 312

Table 202: Singapore exchange rate, 2007–11 312

Table 203: South Africa software market value: $ billion, 2007–11 314

Table 204: South Africa software market category segmentation: $ billion, 2011 315

Table 205: South Africa software market value forecast: $ billion, 2011–16 316

Table 206: South Africa size of population (million), 2007–11 323

Table 207: South Africa gdp (constant 2000 prices, $ billion), 2007–11 323

Table 208: South Africa gdp (current prices, $ billion), 2007–11 323

Table 209: South Africa inflation, 2007–11 324

Table 210: South Africa consumer price index (absolute), 2007–11 324

Table 211: South Africa exchange rate, 2007–11 324

Table 212: South Korea software market value: $ billion, 2007–11 326

Table 213: South Korea software market category segmentation: $ billion, 2011 327

Table 214: South Korea software market geography segmentation: $ billion, 2011 328

Table 215: South Korea software market value forecast: $ billion, 2011–16 329

Table 216: South Korea size of population (million), 2007–11 336

Table 217: South Korea gdp (constant 2000 prices, $ billion), 2007–11 336

Table 218: South Korea gdp (current prices, $ billion), 2007–11 336

Table 219: South Korea inflation, 2007–11 337

Table 220: South Korea consumer price index (absolute), 2007–11 337

Table 221: South Korea exchange rate, 2007–11 337

Table 222: Spain software market value: $ million, 2007–11 339

Table 223: Spain software market category segmentation: $ million, 2011 340

Table 224: Spain software market geography segmentation: $ million, 2011 341

Table 225: Spain software market value forecast: $ million, 2011–16 342

Table 226: Spain size of population (million), 2007–11 349

Table 227: Spain gdp (constant 2000 prices, $ billion), 2007–11 349

Table 228: Spain gdp (current prices, $ billion), 2007–11 349

Table 229: Spain inflation, 2007–11 350

Table 230: Spain consumer price index (absolute), 2007–11 350

Table 231: Spain exchange rate, 2007–11 350

Table 232: Sweden software market value: $ billion, 2007–11 352

Table 233: Sweden software market category segmentation: $ billion, 2011 353

Table 234: Sweden software market geography segmentation: $ billion, 2011 354

Table 235: Sweden software market value forecast: $ billion, 2011–16 355

Table 236: Sweden size of population (million), 2007–11 362

Table 237: Sweden gdp (constant 2000 prices, $ billion), 2007–11 362

Table 238: Sweden gdp (current prices, $ billion), 2007–11 362

Table 239: Sweden inflation, 2007–11 363

Table 240: Sweden consumer price index (absolute), 2007–11 363

Table 241: Sweden exchange rate, 2007–11 363

Table 242: United Kingdom software market value: $ billion, 2007–11 365

Table 243: United Kingdom software market category segmentation: $ billion, 2011 366

Table 244: United Kingdom software market geography segmentation: $ billion, 2011 367

Table 245: United Kingdom software market value forecast: $ billion, 2011–16 368

Table 246: United Kingdom size of population (million), 2007–11 375

Table 247: United Kingdom gdp (constant 2000 prices, $ billion), 2007–11 375

Table 248: United Kingdom gdp (current prices, $ billion), 2007–11 375

Table 249: United Kingdom inflation, 2007–11 376

Table 250: United Kingdom consumer price index (absolute), 2007–11 376

Table 251: United Kingdom exchange rate, 2007–11 376

Table 252: United States software market value: $ billion, 2007–11 378

Table 253: United States software market category segmentation: $ billion, 2011 379

Table 254: United States software market geography segmentation: $ billion, 2011 380

Table 255: United States software market value forecast: $ billion, 2011–16 381

Table 256: United States size of population (million), 2007–11 388

Table 257: United States gdp (constant 2000 prices, $ billion), 2007–11 388

Table 258: United States gdp (current prices, $ billion), 2007–11 388

Table 259: United States inflation, 2007–11 389

Table 260: United States consumer price index (absolute), 2007–11 389

Table 261: United States exchange rate, 2007–11 389

Table 262: International Business Machines Corporation: key facts 390

Table 263: International Business Machines Corporation: key financials ($) 391

Table 264: International Business Machines Corporation: key financial ratios 392

Table 265: Microsoft Corporation: key facts 394

Table 266: Microsoft Corporation: key financials ($) 395

Table 267: Microsoft Corporation: key financial ratios 395

Table 268: Oracle Corporation: key facts 397

Table 269: Oracle Corporation: key financials ($) 398

Table 270: Oracle Corporation: key financial ratios 399

Table 271: SAP AG: key facts 401

Table 272: SAP AG: key financials ($) 402

Table 273: SAP AG: key financials (€) 402

Table 274: SAP AG: key financial ratios 402

Table 275: Hewlett-Packard Company: key facts 404

Table 276: Hewlett-Packard Company: key financials ($) 406

Table 277: Hewlett-Packard Company: key financial ratios 406

Table 278: TOTVS S.A.: key facts 408

Table 279: TOTVS S.A.: key financials ($) 409

Table 280: TOTVS S.A.: key financials (BRL) 409

Table 281: TOTVS S.A.: key financial ratios 410

Table 282: Symantec Corporation: key facts 412

Table 283: Symantec Corporation: key financials ($) 413

Table 284: Symantec Corporation: key financial ratios 414

Table 285: CA Technologies: key facts 416

Table 286: CA Technologies: key financials ($) 417

Table 287: CA Technologies: key financial ratios 417

Table 288: Infosys Limited: key facts 419

Table 289: Infosys Limited: key financials ($) 420

Table 290: Infosys Limited: key financial ratios 421

Table 291: Tata Consultancy Services Limited: key facts 423

Table 292: Tata Consultancy Services Limited: key financials ($) 424

Table 293: Tata Consultancy Services Limited: key financials (Rs.) 425

Table 294: Tata Consultancy Services Limited: key financial ratios 425

Table 295: Visma AS: key facts 427

Table 296: Visma AS: key financials ($) 428

Table 297: Visma AS: key financials (NOK) 428

Table 298: Visma AS: key financial ratios 428

Table 299: Asseco Poland S.A.: key facts 430

Table 300: Asseco Poland S.A.: key financials ($) 432

Table 301: Asseco Poland S.A.: key financials (zl) 432

Table 302: Asseco Poland S.A.: key financial ratios 432

Table 303: The Sage Group plc: key facts 434

Table 304: The Sage Group plc: key financials ($) 435

Table 305: The Sage Group plc: key financials (£) 436

Table 306: The Sage Group plc: key financial ratios 436

To order this report:Software Industry: Software: Global Industry Almanac, MarketLine

Contact
Nicolas Bombourg
Reportlinker
Email: [email protected]
US: (805)652-2626
Intl: +1 805-652-2626

 

SOURCE Reportlinker

More Stories By PR Newswire

Copyright © 2007 PR Newswire. All rights reserved. Republication or redistribution of PRNewswire content is expressly prohibited without the prior written consent of PRNewswire. PRNewswire shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon.

@ThingsExpo Stories
IoT is still a vague buzzword for many people. In his session at Internet of @ThingsExpo, Mike Kavis, Vice President & Principal Cloud Architect at Cloud Technology Partners, will discuss the business value of IoT that goes far beyond the general public's perception that IoT is all about wearables and home consumer services. The presentation will also discuss how IoT is perceived by investors and how venture capitalist access this space. Other topics to discuss are barriers to success, what is new, what is old, and what the future may hold.
The Internet of Things (IoT) is going to require a new way of thinking and of developing software for speed, security and innovation. This requires IT leaders to balance business as usual while anticipating for the next market and technology trends. Cloud provides the right IT asset portfolio to help today’s IT leaders manage the old and prepare for the new. Today the cloud conversation is evolving from private and public to hybrid. This session will provide use cases and insights to reinforce the value of the network in helping organizations to maximize their company’s cloud experience.
Cultural, regulatory, environmental, political and economic (CREPE) conditions over the past decade are creating cross-industry solution spaces that require processes and technologies from both the Internet of Things (IoT), and Data Management and Analytics (DMA). These solution spaces are evolving into Sensor Analytics Ecosystems (SAE) that represent significant new opportunities for organizations of all types. Public Utilities throughout the world, providing electricity, natural gas and water, are pursuing SmartGrid initiatives that represent one of the more mature examples of SAE. We have spoken with, or attended presentations from, utilities in the United States, South America, Asia and Europe. This session will provide a look at the CREPE drivers for SmartGrids and the solution spaces used by SmartGrids today and planned for the near future. All organizations can learn from SmartGrid’s use of Predictive Maintenance, Demand Prediction, Cloud, Big Data and Customer-facing Dashboards...
Whether you're a startup or a 100 year old enterprise, the Internet of Things offers a variety of new capabilities for your business. IoT style solutions can help you get closer your customers, launch new product lines and take over an industry. Some companies are dipping their toes in, but many have already taken the plunge, all while dramatic new capabilities continue to emerge. In his session at Internet of @ThingsExpo, Reid Carlberg, Senior Director, Developer Evangelism at salesforce.com, to discuss real-world use cases, patterns and opportunities you can harness today.
All major researchers estimate there will be tens of billions devices – computers, smartphones, tablets, and sensors – connected to the Internet by 2020. This number will continue to grow at a rapid pace for the next several decades. With major technology companies and startups seriously embracing IoT strategies, now is the perfect time to attend @ThingsExpo in Silicon Valley. Learn what is going on, contribute to the discussions, and ensure that your enterprise is as "IoT-Ready" as it can be!
Noted IoT expert and researcher Joseph di Paolantonio (pictured below) has joined the @ThingsExpo faculty. Joseph, who describes himself as an “Independent Thinker” from DataArchon, will speak on the topic of “Smart Grids & Managing Big Utilities.” Over his career, Joseph di Paolantonio has worked in the energy, renewables, aerospace, telecommunications, and information technology industries. His expertise is in data analysis, system engineering, Bayesian statistics, data warehouses, business intelligence, data mining, predictive methods, and very large databases (VLDB). Prior to DataArchon, he served as a VP and Principal Analyst with Constellation Group. He is a member of the Boulder (Colo.) Brain Trust, an organization with a mission “to benefit the Business Intelligence and data management industry by providing pro bono exchange of information between vendors and independent analysts on new trends and technologies and to provide vendors with constructive feedback on their of...
Software AG helps organizations transform into Digital Enterprises, so they can differentiate from competitors and better engage customers, partners and employees. Using the Software AG Suite, companies can close the gap between business and IT to create digital systems of differentiation that drive front-line agility. We offer four on-ramps to the Digital Enterprise: alignment through collaborative process analysis; transformation through portfolio management; agility through process automation and integration; and visibility through intelligent business operations and big data.
There will be 50 billion Internet connected devices by 2020. Today, every manufacturer has a propriety protocol and an app. How do we securely integrate these "things" into our lives and businesses in a way that we can easily control and manage? Even better, how do we integrate these "things" so that they control and manage each other so our lives become more convenient or our businesses become more profitable and/or safe? We have heard that the best interface is no interface. In his session at Internet of @ThingsExpo, Chris Matthieu, Co-Founder & CTO at Octoblu, Inc., will discuss how these devices generate enough data to learn our behaviors and simplify/improve our lives. What if we could connect everything to everything? I'm not only talking about connecting things to things but also systems, cloud services, and people. Add in a little machine learning and artificial intelligence and now we have something interesting...
Last week, while in San Francisco, I used the Uber app and service four times. All four experiences were great, although one of the drivers stopped for 30 seconds and then left as I was walking up to the car. He must have realized I was a blogger. None the less, the next car was just a minute away and I suffered no pain. In this article, my colleague, Ved Sen, Global Head, Advisory Services Social, Mobile and Sensors at Cognizant shares his experiences and insights.
We are reaching the end of the beginning with WebRTC and real systems using this technology have begun to appear. One challenge that faces every WebRTC deployment (in some form or another) is identity management. For example, if you have an existing service – possibly built on a variety of different PaaS/SaaS offerings – and you want to add real-time communications you are faced with a challenge relating to user management, authentication, authorization, and validation. Service providers will want to use their existing identities, but these will have credentials already that are (hopefully) irreversibly encoded. In his session at Internet of @ThingsExpo, Peter Dunkley, Technical Director at Acision, will look at how this identity problem can be solved and discuss ways to use existing web identities for real-time communication.
Can call centers hang up the phones for good? Intuitive Solutions did. WebRTC enabled this contact center provider to eliminate antiquated telephony and desktop phone infrastructure with a pure web-based solution, allowing them to expand beyond brick-and-mortar confines to a home-based agent model. It also ensured scalability and better service for customers, including MUY! Companies, one of the country's largest franchise restaurant companies with 232 Pizza Hut locations. This is one example of WebRTC adoption today, but the potential is limitless when powered by IoT. Attendees will learn real-world benefits of WebRTC and explore future possibilities, as WebRTC and IoT intersect to improve customer service.
From telemedicine to smart cars, digital homes and industrial monitoring, the explosive growth of IoT has created exciting new business opportunities for real time calls and messaging. In his session at Internet of @ThingsExpo, Ivelin Ivanov, CEO and Co-Founder of Telestax, will share some of the new revenue sources that IoT created for Restcomm – the open source telephony platform from Telestax. Ivelin Ivanov is a technology entrepreneur who founded Mobicents, an Open Source VoIP Platform, to help create, deploy, and manage applications integrating voice, video and data. He is the co-founder of TeleStax, an Open Source Cloud Communications company that helps the shift from legacy IN/SS7 telco networks to IP-based cloud comms. An early investor in multiple start-ups, he still finds time to code for his companies and contribute to open source projects.
The Internet of Things (IoT) promises to create new business models as significant as those that were inspired by the Internet and the smartphone 20 and 10 years ago. What business, social and practical implications will this phenomenon bring? That's the subject of "Monetizing the Internet of Things: Perspectives from the Front Lines," an e-book released today and available free of charge from Aria Systems, the leading innovator in recurring revenue management.
The Internet of Things will put IT to its ultimate test by creating infinite new opportunities to digitize products and services, generate and analyze new data to improve customer satisfaction, and discover new ways to gain a competitive advantage across nearly every industry. In order to help corporate business units to capitalize on the rapidly evolving IoT opportunities, IT must stand up to a new set of challenges.
There’s Big Data, then there’s really Big Data from the Internet of Things. IoT is evolving to include many data possibilities like new types of event, log and network data. The volumes are enormous, generating tens of billions of logs per day, which raise data challenges. Early IoT deployments are relying heavily on both the cloud and managed service providers to navigate these challenges. In her session at 6th Big Data Expo®, Hannah Smalltree, Director at Treasure Data, to discuss how IoT, Big Data and deployments are processing massive data volumes from wearables, utilities and other machines.
P2P RTC will impact the landscape of communications, shifting from traditional telephony style communications models to OTT (Over-The-Top) cloud assisted & PaaS (Platform as a Service) communication services. The P2P shift will impact many areas of our lives, from mobile communication, human interactive web services, RTC and telephony infrastructure, user federation, security and privacy implications, business costs, and scalability. In his session at Internet of @ThingsExpo, Erik Lagerway, Co-founder of Hookflash, will walk through the shifting landscape of traditional telephone and voice services to the modern P2P RTC era of OTT cloud assisted services.
While great strides have been made relative to the video aspects of remote collaboration, audio technology has basically stagnated. Typically all audio is mixed to a single monaural stream and emanates from a single point, such as a speakerphone or a speaker associated with a video monitor. This leads to confusion and lack of understanding among participants especially regarding who is actually speaking. Spatial teleconferencing introduces the concept of acoustic spatial separation between conference participants in three dimensional space. This has been shown to significantly improve comprehension and conference efficiency.
The Internet of Things is tied together with a thin strand that is known as time. Coincidentally, at the core of nearly all data analytics is a timestamp. When working with time series data there are a few core principles that everyone should consider, especially across datasets where time is the common boundary. In his session at Internet of @ThingsExpo, Jim Scott, Director of Enterprise Strategy & Architecture at MapR Technologies, will discuss single-value, geo-spatial, and log time series data. By focusing on enterprise applications and the data center, he will use OpenTSDB as an example to explain some of these concepts including when to use different storage models.
SYS-CON Events announced today that Gridstore™, the leader in software-defined storage (SDS) purpose-built for Windows Servers and Hyper-V, will exhibit at SYS-CON's 15th International Cloud Expo®, which will take place on November 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA. Gridstore™ is the leader in software-defined storage purpose built for virtualization that is designed to accelerate applications in virtualized environments. Using its patented Server-Side Virtual Controller™ Technology (SVCT) to eliminate the I/O blender effect and accelerate applications Gridstore delivers vmOptimized™ Storage that self-optimizes to each application or VM across both virtual and physical environments. Leveraging a grid architecture, Gridstore delivers the first end-to-end storage QoS to ensure the most important App or VM performance is never compromised. The storage grid, that uses Gridstore’s performance optimized nodes or capacity optimized nodes, starts with as few a...
The Transparent Cloud-computing Consortium (abbreviation: T-Cloud Consortium) will conduct research activities into changes in the computing model as a result of collaboration between "device" and "cloud" and the creation of new value and markets through organic data processing High speed and high quality networks, and dramatic improvements in computer processing capabilities, have greatly changed the nature of applications and made the storing and processing of data on the network commonplace. These technological reforms have not only changed computers and smartphones, but are also changing the data processing model for all information devices. In particular, in the area known as M2M (Machine-To-Machine), there are great expectations that information with a new type of value can be produced using a variety of devices and sensors saving/sharing data via the network and through large-scale cloud-type data processing. This consortium believes that attaching a huge number of devic...