The Data Management Survey 22 Analyzer (free version)

Survey Results KPI Dashboard Product Dashboard Product Comparison Documentation

Survey Results

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.



(Premium Version Only)



No. of employees

User type


Which department do you work in?

N = 834

KPI Dashboard

(Demo of the premium version. Contains dummy data.)

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.

KPI filter

Peer group filter

Product Dashboard

(Demo of the premium version. Contains dummy data.)

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.

Product filter

Peer group filter

Product Comparison

(Demo of the premium version. Contains dummy data.)

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.

Peer group



About The Data Management Survey Analyzer

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.

KPIShort explanation
Demographics: CountryCountry
Demographics: DepartmentWhich department do you work in?
Demographics: IndustryIndustry sector
Demographics: Number of product usersNumber of data management product users
Demographics: Number of employeesNumber of employees
Demographics: Percentage of product usersPercentage of product users in company
Demographics: PositionPosition in company
Demographics: RegionRegion
Selection: Chosen productWhich data management product would you like to review?
Selection: Reasons to buyWhy was the product chosen?
Product: RecommendationWould you recommend others to buy your data management product?
Product: TasksFor which tasks do you use your data management tool?
Product: SatisfactionTo what degree are you satisfied with your data management tool?
Product: Usage problemsWhat, if any, are the most serious problems in the use of your product?
Features: AutomationHow would you rate the automation of your product?
Features: ConnectivityHow would you rate the connectivity of your product?
Features: Developer efficiencyHow would you rate the developer efficiency of your product?
Features: FunctionalityHow would you rate the functionality of your product?
Features: Innovative strengthHow would you rate the innovative strength of your product?
Features: PerformanceHow would you rate the performance of your product?
Features: Platform reliabilityHow would you rate the platform reliability of your product?
Features: Price to valueHow would you rate the price to value of your product?
Features: Support qualityHow would you rate the support quality of your product?
Features: Time to marketHow would you rate the time to market of your product?
Features: UsabilityHow would you rate the usability of your product?
Non-product related questions: Initiatives driving investmentsWhat initiatives are driving your data management investments significantly?
Non-product related questions: Investments data managementHow much do you expect/plan to invest in data management this year?
Non-product related questions: Level of benefits from investmentsWhat level of benefits do you expect for the company from its planned investments in data management?
Non-product related questions: Measures being invested inWhat specific measures are being invested in?
Non-product related questions: TrendsWhich data management trends are having the most impact on your data management investments?
Data Warehouse Technologies

Data warehouse technologies prepare, store and provide data for data warehousing purposes.

Products to Support DW Automation

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

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

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

Analytical database products prepare, store and provide data for analytical purposes.

Data Governance Products

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.

ProductNumber of answers
2150 Datavault Builder30
Alation Data Catalog30
Amazon RedShift32
Collibra Data Catalog32
Exasol Database30
Google Big Query31
Informatica EDC30
MS Azure Data Factory31
MS SQL Server78
Oracle Data Integrator32
Oracle Database33
Snowflake CDP26
Synabi D-QUANTUM32
Aggregated KPIsRoot KPIs
Customer SatisfactionPrice to Value
Time to Market
Product Satisfaction
Support Quality
Customer ExperiencePerformance
Platform Reliability
Developer Efficiency
InnovationInnovation Power
Technical CapabilityConnectivity
KPIShort explanation
Price to ValueThis KPI is based on how users rate their tool in terms of price-to-value-ratio.
Time to MarketThis KPI is based on how users rate their tool in terms of adaptability (agility to adapt to new requirements).
RecommendationThis KPI is based on the proportion of users that say they would recommend the product to others.
Product SatisfactionThis KPI is based on the proportion of users that say they are satisfied with their product.
Support QualityThis 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 SatisfactionThis KPI combines the Price to Value, Time to Market, Recommendation, Product Satisfaction and Support Quality KPIs.
PerformanceThis KPI is based on how users rate their tool in terms of performance (query performance, load performance, processing performance).
Platform ReliabilityThis KPI is based on how users rate their tool in terms of platform reliability (i.e., stability, functional reliability, monitoring capabilities).
Developer EfficiencyThis 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).
UsabilityThis KPI is based on how users rate their tool in terms of usability (i.e., ease of use, GUI design, transparency & documentation).
Customer ExperienceThis KPI combines the Performance, Platform Reliability, Developer Efficiency and Usability KPIs.
Innovation PowerThis 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).
AutomationThis 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).
InnovationThis KPI combines the Innovation Power and Automation KPIs.
ConnectivityThis KPI is based on how users rate their tool in terms of connectivity to data sources/targets and interfaces to integrate in ecosystems.
FunctionalityThis KPI is based on how users rate their tool in terms of functionality (i.e., capabilities and functional scope).
Technical CapabilityThis KPI combines the Connectivity and Functionality KPIs.