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DATA PRODUCTS

Transforming Data into Valuable Assets

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The challenge today is making fragmented data trusted and ready for use. Qlik Data Products bridge the gap between producers and consumers by packaging data into managed units (Data as a Product). By bundling transformations, quality rules, and metadata into a single, curated unit, the system simplifies consumption and provides a secure foundation for advanced analytics and AI

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Data Lifecycle Management

Data Lifecycle Management

Qlik Data Products streamlines workflows by providing immediate value and simplifying how data is accessed and consumed by end-users. By treating data as a finished product rather than a raw resource, organizations can eliminate the typical bottlenecks associated with data preparation. This ensures that the right data reaches the right people through a user-friendly interface, ready for immediate analytical use.

  • Easy Access: Makes it easier for users to locate and use high-quality data
  • Immediate Value: Reduces the “grunt work” needed to make data project ready
  • Domain-Centric Approach: Organizes data around specific business functions for increased relevance
Inherent Trust and Data Governance

Inherent Trust and Data Governance

Building trusted data is critical for any analytics strategy. Qlik minimizes risk exposure and compliance challenges by providing detailed quality metrics at both the product and dataset levels. With clear data lineage and transparent provenance, users can confidently rely on the data’s accuracy, knowing exactly where it came from and how it was curated. This ensures full compliance with organizational standards.
  • Verified Quality: Real-time quality scores ensure data meets business standards
  • Transparent Lineage: Full visibility into the data’s journey from source to product
  • Reduced Risk: Built-in governance minimizes compliance burdens and data errors
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Accelerated Business Outcomes and AI Readiness

By aligning data producers and consumers through a unified framework, Qlik Data Products reduces the time-to-value for new use cases by as much as 90%. This architecture provides the essential metadata and curated datasets required to power advanced AI initiatives, such as Retrieval-Augmented Generation (RAG). It ensures that AI models are grounded in diverse, timely, and secure data, leading to more reliable AI-driven results.
  • Faster Implementation: Reduces deployment time for new data-driven projects
  • AI-Ready Foundation: Curates data units specifically designed to fuel GenAI models
  • Lower TCO: Reduces technology and maintenance costs by up to 30% through efficiency

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How organizations create value with Qlik Data Products

Financial Services (Mortgage Industry)

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Financial Services (Mortgage Industry)

Mortgage providers can now transition to defined self-service data products. This will empower loan officers to offer tailored mortgage solutions in real time, while finance teams can achieve better operational agility by accessing trusted data without manual intervention.

Cloud Data Warehousing (Snowflake)

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Cloud Data Warehousing (Snowflake)

Global enterprises can now turn Snowflake datasets into domain-specific data products. By leveraging native push-down features to optimize quality without moving the data, they can now immediately launch analytics apps maximizing the value of their cloud investment.

Legacy System Integration (SAP)

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Legacy System Integration (SAP)

Manufacturing firms can now transform complex SAP data into curated products for “Quote-to-Cash” and inventory use cases. By integrating SAP data with other sources, they gain multi-source insights that drive faster, high-quality decision-making across the supply chain.

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