This screen shows the responses to a single question in The Advanced Analytics Survey. You can choose the question in the dropdown box in the top left corner of the report. The filters to the left of the screen can be used to modify the chart.
N = 582
The KPI Dashboard allows you to compare product results by criteria (KPIs). For each KPI, values are shown for all the products in the peer group selected in the peer group filter. The peer group average is displayed as a gray bar. All products displayed above the gray bar are above average in the peer group, and those below the gray bar are below average. At the top of the screen, you can choose which KPI and peer group to analyze.
This report shows a summary of the KPI results for a single product. The dashboard displays the results for aggregated KPIs in bold and the root KPIs in regular. Simply select a peer group and product in the filters at the top of the screen. The product filter will only display the products in the selected peer group. The peer group filter will only display the peer groups in which the selected product appears.
This screen allows you to make your own short list of products and compare them directly against each other based on multiple criteria. First select a peer group that you want as the basis for the product comparison in the filter. Then select the relevant criteria (KPIs). Multiple KPIs can be selected in this filter. Finally select the products you wish to compare.
The Advanced Analytics Survey Analyzer web app is an interactive tool that enables you to perform your own custom analysis of The Advanced Analytics Survey data. The app contains results from all the questions asked in The Advanced Analytics Survey 19. Product-related results based on a series of important criteria (known here as KPIs – Key Performance Indicators) are also available to view.
Abbreviation | Question | |
---|---|---|
Demographics: Country | Country | |
Demographics: Department | Which department do you work in? | |
Demographics: European regions | European regions | |
Demographics: Industry | Industry sector | |
Demographics: Number of product users | Number of Advanced Analytics product users | |
Demographics: Number of Advanced Analytics users | Number of Advanced Analytics users | |
Demographics: Number of employees | Number of employees | |
Demographics: Percentage of Advanced Analytics users | Percentage of Advanced Analytics users in company | |
Demographics: Position | Position in company | |
Demographics: Region | Region | |
Selection: Acquired products | Which products has your organization acquired? | |
Selection: Chosen product | With which product are you most familiar? | |
Selection: Evaluated products | Which products has your organization evaluated? | |
Selection: Reasons to buy | Why was the product chosen? | |
Selection: Selection type | Did your organization conduct a formal product selection? | |
Implementation: Admin satisfaction (technical) | How would you rate the level of administrator satisfaction with the implementation of technical aspects of your project? | |
Implementation: Project length | How long did it take to implement the advanced analytics software? | |
Implementation: Project on-budget | How would you rate the level of satisfaction with the completion of the project within the budget originally specified? | |
Implementation: Project on-time | How would you rate the level of satisfaction with the completion of the project within the timeframe originally specified? | |
Implementation: User satisfaction (business) | How would you rate the level of user satisfaction with the implementation of business aspects of your project? | |
Implementation: User satisfaction (technical) | How would you rate the level of user satisfaction with the implementation of technical aspects of your project? | |
Implementation: Integration in business processes | How would you rate the level of satisfaction with integration in business processes? | |
Product: Application age | When did your company start using the product? | |
Product: Price-to-value | How would you rate the price-to-value of your advanced analytics product? | |
Product: Usage problems | What, if any, are the most serious problems in the use of your product? | |
Product: Vendor support | How would you rate the level of support provided by the vendor? | |
Product: Recommendation | Would you recommend others to buy your advanced analytics product? | |
Usage: Data variety | Which of the following data sources/formats does your company access? | |
Usage: Data preparation | Which of the following data preparation capabilities does your company use? | |
Usage: Use cases | Which of the following use cases does your company use? | |
Capabilities: User guidance capabilities | How would you rate the governance capabilities of your product? | |
Capabilities: Governance capabilities | How would you rate the user guidance capabilities of your product? | |
Capabilities: Collaborative capabilities | How would you rate the collaborative capabilities of your product? | |
Capabilities: Possibilities to implement analytical models | How would you rate the possibilities to implement analytical models? | |
Capabilities: Functionality | How would you rate the functionality for data preparation, visualization and machine learning of your product? | |
Tasks: Advanced analysis | Do you use or plan to use your product for advanced analysis? | |
Tasks: Visual analysis/data exploration | Do you use or plan to use your product for visual analysis/data exploration? | |
Tasks: Data visualization | Do you use or plan to use your product for data visualization? | |
Tasks: Data access | Do you use or plan to use your product for data access? | |
Tasks: Data manipulation/data prep | Do you use or plan to use your product for data manipulation/data preparation? | |
Tasks: Data profiling | Do you use or plan to use your product for data profiling? | |
Tasks: Classification | Do you use or plan to use your product for classification? | |
Tasks: Clustering | Do you use or plan to use your product for clustering? | |
Tasks: Time series analysis | Do you use or plan to use your product for time series analysis? | |
Tasks: Deployment/Scoring | Do you use or plan to use your product for deployment/scoring? | |
Tasks: Model management | Do you use or plan to use your product for model management? | |
Benefits: Improved time to insight | To what extent has time to insight improved? | |
Benefits: Better quality of analytical results | To what extent has the quality of analytical results improved? | |
Benefits: Increased transparency of data usage | To what extent has the transparency of data usage improved? | |
Benefits: Use/re-use of analytical insights | To what extent has the re-use and use of analytical insights improved? | |
Benefits: Reduced resource requirements | To what extent have resource requirements decreased? | |
Benefits: Improved employee satisfaction | To what extent has your employee satisfaction improved? | |
Benefits: Saved headcount | To what extent have you saved on headcount in business departments or IT? | |
Benefits: Reduced costs | To what extent have you reduced costs? (IT or non-IT) | |
Non-commercial products: Application age | When did your company start using the product? | |
Non-commercial products: Acquired products | Which products has your organization acquired? | |
Non-commercial products: Admin satisfaction (technical) | How would you rate the level of administrator satisfaction with the implementation of technical aspects of your project? | |
Non-commercial products: Chosen product | With which product are you most familiar? | |
Non-commercial products: Evaluated products | Which products has your organization evaluated? | |
Non-commercial products: Price-to-value | How would you rate the price-to-value of your product? | |
Non-commercial products: Problems | What, if any, are the most serious problems in the use of your product? | |
Non-commercial products: Project length | How do you rate the level of administrator satisfaction with the implementation of technical aspects of your project? | |
Non-commercial products: Project on-budget | How would you rate the level of satisfaction with the completion of the project within the budget originally specified? | |
Non-commercial products: Project on-time | How would you rate the level of satisfaction with the completion of the project within the timeframe originally specified? | |
Non-commercial products: Reasons to buy | Why was your your product chosen? | |
Non-commercial products: Recommendation | Would you recommend others to buy your advanced analytics product? | |
Non-commercial products: Integration in business processes | How would you rate the level of satisfaction with integration in business processes? | |
Non-commercial products: User satisfaction (business) | How would you rate the level of user satisfaction with the implementation of business aspects of your project? | |
Non-commercial products: User satisfaction (technical) | How would you rate the level of user satisfaction with the implementation of technical aspects of your project? | |
Non-commercial products benefits: Better quality of analytical results | To what extent has the quality of analytical results improved? | |
Non-commercial products benefits: Improved employee satisfaction | To what extent has your employee satisfaction improved? | |
Non-commercial products benefits: Improved time to insight | To what extent has time to insight improved? | |
Non-commercial products benefits: Increased transparency of data usage | To what extent has the transparency of data usage improved? | |
Non-commercial products benefits: Use/Re-use of analytical insights | To what extent has the re-use and use of analytical insights improved? | |
Non-commercial products benefits: Reduced costs | To what extent have you reduced costs? (IT or non-IT) | |
Non-commercial products benefits: Reduced resource requirements for analytics | To what extent have resource requirements decreased? | |
Non-commercial products benefits: Saved headcount | To what extent have you saved on headcount in business departments or IT? | |
Non-commercial products capabilities: Collaborative capabilities | How would you rate the collaborative capabilities of your product? | |
Non-commercial products capabilities: Functionality | How would you rate the functionality for data preparation, visualization and machine learning of your product? | |
Non-commercial products capabilities: Governance capabilities | How would you rate the governance capabilities of your product? | |
Non-commercial products capabilities: Implementation of analytical models | How would you rate the possibilities to implement analytical models? | |
Non-commercial products capabilities: User guidance capabilities | How would you rate the user guidance capabilities of your product? | |
Non-commercial products tasks: Advanced analysis | Do you use or plan to use your product for advanced analysis? | |
Non-commercial products tasks: Classification | Do you use or plan to use your product for classification? | |
Non-commercial products tasks: Clustering | Do you use or plan to use your product for clustering? | |
Non-commercial products tasks: Data access | Do you use or plan to use your product for data access? | |
Non-commercial products tasks: Data manipulation/data preparation | Do you use or plan to use your product for data manipulation/data preparation? | |
Non-commercial products tasks: Data profiling | Do you use or plan to use your product for data profiling? | |
Non-commercial products tasks: Data visualization | Do you use or plan to use your product for data visualization? | |
Non-commercial products tasks: Deployment/Scoring | Do you use or plan to use your product for deployment/scoring? | |
Non-commercial products tasks: Model management | Do you use or plan to use your product for model management? | |
Non-commercial products tasks: Time series analysis | Do you use or plan to use your product for time series analysis? | |
Non-commercial products tasks: Visual analysis/data exploration | Do you use or plan to use your product for visual analysis/data exploration? | |
Non-commercial products usage: Data preparation | Which of the following data preparation capabilities does your company use? | |
Non-commercial products usage: Data variety | Which of the following data sources/formats does your company access? | |
Non-commercial products usage: Use cases | Which of the following use cases does your company use? | |
Trends: Cloud use | Do you currently use a cloud-based advanced analytics, data discovery or data preparation solution, or can you imagine doing so? | |
Trends: Reasons not to use cloud | What are the most important reasons for not using cloud-based tools? | |
Trends: Reasons to use cloud | What are the main reasons for using or wanting to use a cloud-based solution? | |
Trends: Deep learning | In the context of digitalization, how important is deep learning to your company's success? | |
Trends: Predictive maintenance | In the context of digitalization, how important is predictive maintenance to your company's success? | |
Trends: Artificial intelligence/cognitive applications | In the context of digitalization, how important are artificial intelligence/cognitive applications to your company's success? | |
Trends: Data literacy | In the context of digitalization, how important is data literacy to your company's success? | |
Trends: Prescriptive analytics | In the context of digitalization, how important is prescriptive analytics to your company's success? | |
Trends: Automated machine learning | In the context of digitalization, how important is automated machine learning to your company's success? |
Advanced analytics is a generic term for analysis based on mathematical models. Its aim is to identify relationships between variables in order to derive insights from existing data (patterns) as well as new data (forecasts). This peer group contains advanced analytics platforms that provide a broad range of algorithms. They also offer data preparation and visualization functionality, together with options for model deployment.
Data discovery is the business user/analyst driven process of discovering patterns and outliers in data. This peer group includes products that focus on all the sub-elements of data discovery: data preparation, visual analysis and guided advanced analytics.
Data preparation is the process of cleaning, structuring and enriching data for use in data discovery and/or advanced analytics. This peer group includes products and vendors that support these tasks.
The ‘Software generalists’ peer group includes products which are part of a vendor‘s broader business software portfolio. Customers that standardize on such vendors may be more inclined to select their standard provider’s solutions.
Product | Number of answers |
---|---|
Alteryx | 35 |
Dataiku | 32 |
IBM SPSS/WS | 19 |
IBM SPSS/WS/CA | 26 |
Microsoft Azure/SQL Server | 36 |
Microsoft Power BI | 44 |
Qlik | 21 |
RapidMiner | 21 |
SAS | 28 |
Tableau | 24 |
Aggregated KPIs | Root KPIs |
---|---|
Business value | Business benefits |
Project success | |
Project length | |
Customer satisfaction | Price-to-value |
Recommendation | |
Vendor support | |
Product satisfaction | |
User experience | Ease of use |
Code-free usage | |
User guidance | |
Collaboration | |
Openness | |
Data management | Performance satisfaction |
Data volume | |
Data variety | |
Governance | |
Analytics | Data preparation |
Data visualization | |
Visual analysis | |
Advanced analytics breadth | |
Operationalization | Model management |
Model scoring |
KPI | Short explanation |
---|---|
Business benefits | This KPI is based on the achievement level of a variety of business benefits. |
Project success | This KPI is based on the implementation satisfaction level and the frequency of projects completed on time and on budget. |
Project length | This KPI is based on how quickly the product is implemented. |
Business value | This KPI combines the ‘Business benefits’, ‘Project success’ and ‘Project length’ KPIs. |
Price-to-value | This KPI is based on how users rate their software in terms of price-to-value ratio. |
Recommendation | This KPI is based on the proportion of users that say they would recommend the product to others. |
Vendor support | This KPI measures user satisfaction with the level of vendor support provided for the product. |
Product satisfaction | This KPI is based on the frequency of problems encountered with the product. |
Customer satisfaction | This KPI combines the ‘Price-to-value’, ‘Recommendation’, ‘Vendor support’ and ‘Product satisfaction’ KPIs. |
Ease of use | This KPI is based on how often the product was chosen for its ease of use, and on the level of complaints about ease of use post-implementation. |
Code-free usage | This KPI is based on how often the product was chosen for its code-free environment. |
User guidance | This KPI measures user satisfaction with the on-screen guidance the software offers to users. |
Collaboration | This KPI measures user satisfaction with the software‘s collaboration capabilities. |
Openness | This KPI is based on how often the product was chosen for its openness to other programming languages. |
User experience | The ‘User experience’ KPI combines the ‘Ease of use’, ‘Code-free usage’, ‘User guidance’, ‘Collaboration’ and ‘Openness’ KPIs. |
Performance satisfaction | This KPI measures the frequency of complaints about the system’s performance. |
Data volume | This KPI is based on how often the product was chosen for its ability to handle large data volumes. |
Data variety | This KPI is based on the variety of data sources and formats the software is used with. |
Governance | This KPI measures user satisfaction with the software‘s governance capabilities. |
Data management | This KPI combines the ‘Performance satisfaction’, ‘Data volume’, ‘Data variety’ and ‘Governance’ KPIs. |
Data preparation | This KPI is based on the variety of data preparation steps the software is used for. |
Data visualization | This KPI measures the extent to which the software is used for data visualization. |
Visual analysis | This KPI measures the extent to which the software is used for visual analysis. |
Advanced analytics breadth | This KPI measures the breadth of analytical applications the software is used for. |
Analytics | This KPI combines the ‘Data preparation’, ‘Data visualization’, ‘Visual analysis’ and ‘Advanced analytics breadth’ KPIs. |
Model scoring | This KPI measures the extent to which the software is used for model scoring. |
Model management | This KPI measures the extent to which the software is used for model management. |
Operationalization | This KPI combines the ‘Model scoring’ and ‘Model management’ KPIs. |