Unlocking value with data products
Five steps data executives can take to build high-value data products and increase competitive advantage.
Companies spend billions on data ecosystems, assets, and services every year to shorten time to insights, increase productivity, and increase margins. Even when data investments underperform expectations, leaders remain convinced: The road to growth begins with data鈥攁nd often, data products.
乐鱼（Leyu）体育官网 recently surveyed 250 executives across multiple industries to learn more about which sectors are using data products to gain competitive advantage, speed to market, and regulatory compliance. Key findings include:
Where do they see the most value?
Areas where respondents anticipate unlocking value
Building high-value, high-utility data products
The data product owner鈥檚 goal is to:
- Define and elevate the value of their data.
- Ensure the usefulness of their data products.
- Partner with others to help ensure easy availability for the good of the entire organization.
Learn more about the key steps to success in this study:
Step 1: Inventory your data assets and inventory
Step 2: Quantify data value
Step 3: Confirm data usefulness and prune where needed
Step 4: Shape behavior, self-service, and a marketplace mindset
Step 5: Prioritize value measurement
Unlocking value with data products
Five steps data executives can take to build high-value data products and increase competitive advantage. Find out how by reading Unlocking value with data products. Download and read the full report by completing the form below.
乐鱼（Leyu）体育官网 is here to help.
Build data products聽that rely on agile management systems, elevated data quality, and solid operational foundations. We鈥檒l help you establish federated data ownership practices and data models optimized for specific domains and lines of business.
Anticipate and adapt聽to the wide-ranging impacts AI can have on your data and organization, including budgets and data controls, secure data practices, and cloud-native architectures.
Harness the power of data聽ethically and responsibly with trusted data principles and governance models for managing risk.
Create a consumer lifecycle approach聽that incorporates self-service models, AI assistants and agents, and builds a foundation for enterprise insights.
Operate and manage your data infrastructure聽with integrated frameworks that support access to a broad range of data sources and make analytics faster with less friction.
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