This screen shows the responses to a single question in The Data Management 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 = 834
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. 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 Data Management Survey Analyzer web app is an interactive tool that enables you to perform your own custom analysis of The Data Management Survey data. The app contains results from all the questions asked in The Data Management Survey 22. Product-related results based on a series of important criteria (known here as KPIs – Key Performance Indicators) are also available to view.
|Demographics: Department||Which department do you work in?|
|Demographics: Industry||Industry sector|
|Demographics: Number of product users||Number of data management product users|
|Demographics: Number of employees||Number of employees|
|Demographics: Percentage of product users||Percentage of product users in company|
|Demographics: Position||Position in company|
|Selection: Chosen product||Which data management product would you like to review?|
|Selection: Reasons to buy||Why was the product chosen?|
|Product: Recommendation||Would you recommend others to buy your data management product?|
|Product: Tasks||For which tasks do you use your data management tool?|
|Product: Satisfaction||To what degree are you satisfied with your data management tool?|
|Product: Usage problems||What, if any, are the most serious problems in the use of your product?|
|Features: Automation||How would you rate the automation of your product?|
|Features: Connectivity||How would you rate the connectivity of your product?|
|Features: Developer efficiency||How would you rate the developer efficiency of your product?|
|Features: Functionality||How would you rate the functionality of your product?|
|Features: Innovative strength||How would you rate the innovative strength of your product?|
|Features: Performance||How would you rate the performance of your product?|
|Features: Platform reliability||How would you rate the platform reliability of your product?|
|Features: Price to value||How would you rate the price to value of your product?|
|Features: Support quality||How would you rate the support quality of your product?|
|Features: Time to market||How would you rate the time to market of your product?|
|Features: Usability||How would you rate the usability of your product?|
|Non-product related questions: Initiatives driving investments||What initiatives are driving your data management investments significantly?|
|Non-product related questions: Investments data management||How much do you expect/plan to invest in data management this year?|
|Non-product related questions: Level of benefits from investments||What level of benefits do you expect for the company from its planned investments in data management?|
|Non-product related questions: Measures being invested in||What specific measures are being invested in?|
|Non-product related questions: Trends||Which data management trends are having the most impact on your data management investments?|
Data warehouse technologies prepare, store and provide data for data warehousing purposes.
Products in this peer group support data-driven or requirements-driven data warehouse design and implementation. They mainly focus on the simplification and automation of data integration and data modeling tasks.
Data pipelining products take a modern approach to data integration and support more than one data integration pattern. A pattern can be data interaction, data integration, data preparation or even data orchestration in order to get data connected and to make it usable for any kind of business purpose.
Business software generalists have a broad product portfolio including most (or all) types of enterprise software for a variety of business requirements (e.g., ERP, BI, DM).
Analytical database products prepare, store and provide data for analytical purposes.
Data governance products help to control, develop, monitor and secure data to make it usable for business needs. They do not manipulate data. Instead, they focus on managing and leveraging metadata such as data catalogs.
|Product||Number of answers|
|2150 Datavault Builder||30|
|Alation Data Catalog||30|
|Collibra Data Catalog||32|
|Google Big Query||31|
|MS Azure Data Factory||31|
|MS SQL Server||78|
|Oracle Data Integrator||32|
|SAP BW on HANA||31|
|Aggregated KPIs||Root KPIs|
|Customer Satisfaction||Price to Value|
|Time to Market|
|Price to Value||This KPI is based on how users rate their tool in terms of price-to-value-ratio.|
|Time to Market||This KPI is based on how users rate their tool in terms of adaptability (agility to adapt to new requirements).|
|Recommendation||This KPI is based on the proportion of users that say they would recommend the product to others.|
|Product Satisfaction||This KPI is based on the proportion of users that say they are satisfied with their product.|
|Support Quality||This KPI is based on how users rate their tool in terms of support quality (e.g., availability, geographic coverage, support channels, effectiveness and efficiency, reaction time).|
|Customer Satisfaction||This KPI combines the Price to Value, Time to Market, Recommendation, Product Satisfaction and Support Quality KPIs.|
|Performance||This KPI is based on how users rate their tool in terms of performance (query performance, load performance, processing performance).|
|Platform Reliability||This KPI is based on how users rate their tool in terms of platform reliability (i.e., stability, functional reliability, monitoring capabilities).|
|Developer Efficiency||This KPI is based on how users rate their tool in terms of developer efficiency (e.g., for testing, deployment, reusability, ease of coding and use of metadata).|
|Usability||This KPI is based on how users rate their tool in terms of usability (i.e., ease of use, GUI design, transparency & documentation).|
|Customer Experience||This KPI combines the Performance, Platform Reliability, Developer Efficiency and Usability KPIs.|
|Innovation Power||This KPI is based on how users rate their tool in terms of innovative strength (i.e., amount of innovative functionality in the tool, market trend adoption time and rate).|
|Automation||This KPI is based on how users rate their tool in terms of its support for the automation of recurring processes (e.g., by utilizing ML).|
|Innovation||This KPI combines the Innovation Power and Automation KPIs.|
|Connectivity||This KPI is based on how users rate their tool in terms of connectivity to data sources/targets and interfaces to integrate in ecosystems.|
|Functionality||This KPI is based on how users rate their tool in terms of functionality (i.e., capabilities and functional scope).|
|Technical Capability||This KPI combines the Connectivity and Functionality KPIs.|