Qlik Compose® For Data Lakes
Experience the quickest route to analytics-ready data lakes with our streamlined solution.
Automate Analytics-Ready Data Pipelines with Ease
Streamline your data processes by automating the creation of analytics-ready data sets. This includes automating data ingestion, schema creation, and ensuring continual updates to keep your data pipelines in sync and ready for analysis.
2023 Gartner® Magic Quadrant™ for Data Integration Tools
See why Qlik® and Talend® are Leaders in the Gartner Magic Quadrant for Data Integration Tools.
Simplify Data Structuring and Transformation
Effortlessly construct, model, and execute data lake pipelines using an intuitive guided user interface. Say goodbye to manual coding, as you can automatically generate schemas and Hive Catalog structures for both operational data stores (ODS) and historical data stores (HDS).
Change Data Capture (CDC):
Enable real-time analytics with reduced administrative and processing overhead.
Efficient Initial Loading:
Improve efficiency by employing parallel threading for initial data loading.
Time-Based Partitioning:
Process only transactions completed within a specified time frame, ensuring transactional consistency.
Receive Continuous Updates with Confidence
Ensure that your operational data stores (ODS) and historical data stores (HDS) accurately reflect your source systems through continuous updates.
Create Cost-Effective Low Latency Views of Live Data
Optimize your data processing by merging the latest unprocessed changes in the change table (including the last open partition) on Read. This approach allows you to generate cost-effective, low-latency views of live data without the need to process changes every time, enhancing overall efficiency.
Automatic Time-Stamping:
Automatically time-stamp new HDS records, enabling trend analysis and other time-oriented analytic data marts.
Support for Data Models:
Support data models that include Type-2, slowing changing dimensions, enhancing the accuracy and completeness of your analytics.
Create Analytics-Specific Data Sets from Historical Data Store (HDS)
Effortlessly generate analytics-specific data sets from a full historical data store (HDS) by automating the appending of new rows as data updates arrive from source systems.
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