Accelerate and simplify data warehouse design, development, testing, deployment, and updates.
KEY RESOURCE
2024 Gartner® Magic Quadrant™ for Data Integration Tools
See why Qlik® is a Leader in the Gartner Magic Quadrant for Data Integration Tools.
Speed time to analytics
The traditional multi-month, error prone ETL development to set up a data warehouse — typically 60 – 80% of prep time — often means your data model is out of date before the BI project even starts.
To speed time to analytics, you need to streamline data warehouse creation and management lifecycle.
Take a modern approach to data warehousing
Qlik Compose automates designing the warehouse, generating ETL code, and quickly applying updates, and leverages best practices and proven design patterns. You can dramatically reduce the time, cost, and risk of BI projects, on-premises or in the cloud.
Dramatically reduce time, costs, and risks of data warehousing
Quickly design, create, load and update data warehouses
Automatically generate ETL to reduce time, costs and risks
Implement best practices and templates for more effective BI projects
Reduce dependence on highly technical development resources
Automatically generate end-to-end workflows from data ingest to report generation
Enjoy intuitive and guided workflows
Load and sync data with ease. Source feeds are loaded in real time with change data capture (CDC).
Automate data model design and source mapping. Data models can be created or imported, then modified and enhanced iteratively.
Streamline data warehouse and ETL generation. ETL code is auto generated to populate and load data warehouses.
Deploy data marts without manual coding. Data mart types are selected from a broad array of options including transactional, aggregated, or state oriented.
Optimize the data warehousing process
Workflow Designer and Scheduler: Run data warehouse and data mart ETL tasks as a single, end-to-end process. Schedule the execution of workflows to align with business and IT processes.
Lineage and Impact Analysis: Automatically create metadata during design phases or implementation. Re-generate data lineage when changes are implemented.
Monitoring and Notification: Monitor the status of all automatically generated tasks and workflows. Send proactive status alerts.
Data Profiling: Validate data before it is loaded by identifying and repairing format issues and discrepancies.
Data Quality: Configure and enforce pre-loading rules to automatically discover and remediate issues with values, formats, data ranges, and duplication while also implementing exception policies.
DataOps for analytics
Get real time, analytics-ready, and actionable data to an analytics environment, from Qlik to Tableau, Power BI and beyond.
