BeyeNETWORK: Global coverage of the business intelligence ecosystem
The BI Survey 7 - Charts and tables

The BI Survey 7 - Charts and tables

To return to the Product Overview, click here

Figure 1

Charting example

Figure 2

Illustrating means and quartiles

Figure 3

Recommended Survey invitation wording

Figure 4

Sample make-up

Figure 5

Purchase rates

Figure 6

Respondents‚ roles overall

Figure 7

Respondents‚ roles by product, vendor, architecture

Figure 8

Respondents‚ roles by fees, volumes, organization

Figure 9

Geographic trend of The BI/OLAP Surveys

Figure 10

Location of respondents‚ parent organizations

Figure 11

Geographic scope of respondents‚ organizations

Figure 12

Organization total revenues

Figure 13

Organization size by employees

Figure 14

Industry sector analysis

Figure 15

Industry sector analysis by product

Figure 16

Industry sector analysis by multi-product vendor

Figure 17

Products included in the sample

Figure 18

Augmented samples

Figure 19

Usage levels of SAP BI/BW ŒBusiness Content‚

Figure 20

Percentage of data originating from SAP ERP

Figure 21

SAP BI Accelerator usage and plans

Figure 22

The architectural mix

Figure 23

Time since purchase

Figure 24

Age profiles

Figure 25

Comparing product mixes in mature and recent sites

Figure 26

How did you compile a list of BI products to evaluate?

Figure 27

Influences by products evaluated

Figure 28

Influences by license fees, platforms and data volumes

Figure 29

Influences by organization demographics

Figure 30

Relative influence of industry analysts

Figure 31

Product shares by analyst influence

Figure 32

BBI by analyst influence

Figure 33

Goals and benefits achieved vs selection method

Figure 34

Evaluation trends

Figure 35

Reasons given for choosing BI products

Figure 36

Reasons for choosing products by type of respondent

Figure 37

Reasons for choosing different products

Figure 38

Aggregated reasons for choosing different products

Figure 39

Reasons for product selection by organization demography

Figure 40

Aggregated reasons for product selection by organization demography

Figure 41

Benefits-driven ranking of selection criteria

Figure 42

License fee distribution

Figure 43

License fees by respondent type

Figure 44

License fees by product, vendor and architecture

Figure 45

License fees by evaluation method, deployment and platform

Figure 46

License fees by implementation

Figure 47

License fees by demography

Figure 48

Goals and benefits vs license fees

Figure 49

Proportion of employees using BI applications

Figure 50

Proportion of users by respondent type

Figure 51

Proportion of users by product, vendor and architecture

Figure 52

Proportion of users by timing, license, implementer, volumes

Figure 53

Proportion of users by organization demography

Figure 54

Departments using BI by product

Figure 55

Departments using BI by organization demography

Figure 56

Net people involved in running and administering projects

Figure 57

Overall achievement of business goals

Figure 58

Achievement of business goals, analyzed by product and vendor

Figure 59

Achievement of business goals, analyzed by product and vendor

Figure 60

Goal achievement scores, analyzed by age

Figure 61

Product goal achievement scores vs age

Figure 62

Benefit weightings

Figure 63

Weighted benefit achievement levels

Figure 64

Overall BBI calculation

Figure 65

Trends in reported benefits

Figure 66

BBI analyzed by product and vendor

Figure 67

The BBI score trend analyzed by product

Figure 68

BBI analyzed by architecture, selection, age, distribution

Figure 69

BBI analyzed by Web deployment rates and license fees

Figure 70

BBI analyzed by implementation factors

Figure 71

BBI analyzed by customer demography

Figure 72

Cost of Ownership Index

Figure 73

Analysis of chances of products being evaluated

Figure 74

Evaluation frequency trend

Figure 75

Likelihood of a formal evaluation

Figure 76

Vendors most often encountered in competitive sales

Figure 77

Win rates, including and excluding non-buyers

Figure 78

Selection rates by evaluation type

Figure 79

Win rate trends in recent and mature projects

Figure 80

Win rates by organization size

Figure 81

Win rates by organization location

Figure 82

Customer demographics

Figure 83

Unlimited license analysis by product

Figure 84

Seats sold, excluding unlimited licenses

Figure 85

Average and median deployed seats

Figure 86

Percentages of sites with large numbers of deployed seats

Figure 87

Prevalence rates in organizations

Figure 88

Shelfware rates

Figure 89

Likelihood of deploying all seats within 12 months

Figure 90

Inclination to buy more seats

Figure 91

Buying intentions "Positive gap" trend

Figure 92

Primary support method trend

Figure 93

Analysis of primary support methods

Figure 94

Overall ratings of product support

Figure 95

Support ratings by method

Figure 96

Support quality ratings by product

Figure 97

Product support scores trend

Figure 98

Support quality ratings by vendor size

Figure 99

Support quality ratings by type of respondent

Figure 100

Product support rating vs license fees paid and evaluation method

Figure 101

Discontinued usage analysis

Figure 102

The possible effects of standardization preferences

Figure 103

Preferred products to retain when standardizing

Figure 104

Reasons given for standardization

Figure 105

The product loyalty league table

Figure 106

Loyalty scores trend

Figure 107

All the implementation resources used

Figure 108

The primary implementation resource

Figure 109

The implementation mix by product and vendor

Figure 110

The implementation mix by architecture, volumes and demographics

Figure 111

Implementation fee distribution

Figure 112

Implementation fees trend

Figure 113

Implementation spend by respondent type and analyst

Figure 114

Implementation spend by product, architecture and volumes

Figure 115

Implementation spend by license fees, and implementation factors

Figure 116

Implementation costs compared to license fees

Figure 117

Implementation spend by organization demography

Figure 118

Benefits vs external consulting spend

Figure 119

Benefits vs primary implementation resource

Figure 120

Implementation time distribution

Figure 121

Project success rates by implementation time

Figure 122

Problem rates by implementation time

Figure 123

Implementation times by product and vendor

Figure 124

Implementation times by environment

Figure 125

Implementation times by organization demographics

Figure 126

Implemented within six months

Figure 127

Problem categories

Figure 128

Reported problem rates by respondent type

Figure 129

Differing perceptions of problem areas

Figure 130

Problem levels by age of project

Figure 131

Problem trends since 2002

Figure 132

Most-serious problem trends in The BI/OLAP Surveys

Figure 133

People problems by rollout times

Figure 134

People problems analyzed by organization demographics

Figure 135

Reported incidence of data problems by product and data volume

Figure 136

Product-related problems analysis

Figure 137

Product-related problems by version

Figure 138

Product-related problems by input data volume

Figure 139

Product-related problems by lead implementer

Figure 140

Environmental problems

Figure 141

Normalized product-related problems

Figure 142

Analyzing the problem mix by product and architecture

Figure 143

Analyzing the problem mix by respondent and implementers

Figure 144

Analyzing the problem mix by data volumes and demographics

Figure 145

Deterrents to wider deployment, by respondent type

Figure 146

Deterrents to wider deployment, by product and vendor

Figure 147

Deterrents analyzed by architecture, license fees and platform

Figure 148

Deterrents analyzed by implementation leader and time

Figure 149

No deterrents to wider deployment

Figure 150

Applications categorized

Figure 151

Application analysis by role and industry analyst

Figure 152

Application analysis by product and vendor

Figure 153

Application analysis by architecture and purchase characteristics

Figure 154

Application analysis by platform, volumes and implementer

Figure 155

Application analysis by organization demographics

Figure 156

Percentage of Web deployed seats from 2001 to 2007

Figure 157

Web deployment trend vs forecasts

Figure 158

Web deployment analysis by respondent and organization

Figure 159

Web deployment analysis by product and vendor

Figure 160

Web deployment analysis by selection and implementation

Figure 161

Web deployment analysis by application

Figure 162

Web deployment trends by product

Figure 163

Reported success rates by Web deployment rates

Figure 164

Extranet plans

Figure 165

Extranet rate trends: perception vs reality

Figure 166

Extranet analysis by product, vendor and architecture

Figure 167

Extranet analysis by platform, implementation and demographics

Figure 168

Extranet target trend

Figure 169

Extranet targets by product factors

Figure 170

Extranet targets by demographic factors

Figure 171

Internet browsers in use

Figure 172

Browsers by product, vendor, source and platform

Figure 173

Browsers by organization demography

Figure 174

Preferred Web browser architectures

Figure 175

Preferred Web architectures by product factors

Figure 176

Preferred Web architectures by organization factors

Figure 177

Server platforms

Figure 178

Overall server platforms trend

Figure 179

Detailed platform trends, 2001-2007

Figure 180

Platform analysis by product, vendor and architecture

Figure 181

Platform analysis by input data volumes

Figure 182

Platform analysis by organization factors

Figure 183

Platform analysis by organization factors

Figure 184

Business benefits and goal achievement analysis by platform

Figure 185

32-bit and 64-bit server distribution analyzed by product factors

Figure 186

32-bit and 64-bit server distribution by organization demography

Figure 187

Analysis Services client tools

Figure 188

Essbase client tools

Figure 189

SAP BI/BW client tools

Figure 190

TM1 client tools

Figure 191

Comparing the OLAP server client tools markets

Figure 192

Data sources accessed by arcplan

Figure 193

Data sources accessed by BusinessObjects and Crystal

Figure 194

Data sources accessed by Cognos front-end tools

Figure 195

Data sources accessed by Cubeware Cockpit

Figure 196

Data sources accessed by WebFOCUS

Figure 197

Data sources accessed by Microsoft PivotTables and Reporting Services

Figure 198

Average number of data sources accessed by BI client tools

Figure 199

Source databases for BI applications

Figure 200

Database sources for BI data

Figure 201

Data sources by input data volume bands

Figure 202

Data sources by product and vendor

Figure 203

Data sources by product type and platform

Figure 204

Data sources by organization demography

Figure 205

Top ten purchased BI tools in Microsoft database sites

Figure 206

Top five multi-product BI vendors in Microsoft database sites

Figure 207

Top ten purchased BI tools in Oracle database sites

Figure 208

Top five multi-product BI vendors in Oracle database sites

Figure 209

Top ten purchased BI tools in IBM database sites

Figure 210

Top five multi-product BI vendors in IBM database sites

Figure 211

Top ten purchased BI tools in Sybase database sites

Figure 212

Top five multi-product BI vendors in Sybase database sites

Figure 213

Top ten purchased BI tools in Teradata sites

Figure 214

Top five multi-product BI vendors in Teradata sites

Figure 215

Top ten purchased BI tools in sites performing manual data entry

Figure 216

Top five multi-product BI vendors in manual data entry sites

Figure 217

Reported input data volumes

Figure 218

Trend of median input data volumes

Figure 219

Median input data volume trend for three major products

Figure 220

Reported mean input data volumes by product

Figure 221

Median and quartile analysis of data volumes by product

Figure 222

Changes in relative market shares with data volumes

Figure 223

Mean, median and quartile analysis of data volumes by platform

Figure 224

Mean, median and quartile analysis of data volumes by 32- vs 64-bit

Figure 225

Reported input data volumes by architecture

Figure 226

Reported input data volumes by lead implementer

Figure 227

Reported input data volumes by industry sector

Figure 228

Reported input data volumes by customer demographic

Figure 229

License fees by input data volume band

Figure 230

Support quality, goals and benefits vs input data volumes

Figure 231

Performance problems compared to other product-related problems

Figure 232

Goals and business benefits vs query performance

Figure 233

Complaints vs query performance

Figure 234

Comparing reported query times since 2002

Figure 235

Quartile analysis of query times

Figure 236

Median query time trend

Figure 237

Median query times vs median input data volumes

Figure 238

Performance complaints

Figure 239

Query times vs volumes trend

Figure 240

Query times vs complaints

Figure 241

Deterrents to wider deployment

Figure 242

Poor query performance as a deterrent to wider deployment

Figure 243

Network bandwidth as a deterrent to wider deployment

Figure 244

Reported median typical query times by architecture

Figure 245

Reported median typical query times by platform

Figure 246

Goals and business benefits vs load/calculate times

Figure 247

Data latency by product and vendor

Figure 248

Data latency by architecture and data volumes

Figure 249

Median latency times vs median input data volumes

Figure 250

Reported median latency times by architecture