Compose

Advanced data lake and data warehouse automation

Qlik Compose for Data Lakes

Your fastest way to analytics-ready data lakes

Automate analytics-ready data pipelines

Qlik Compose for Data Lakes (formerly Attunity Compose) automates your data pipelines to create analytics-ready data sets. By automating data ingestion, schema creation, and continual updates, organizations realize faster time-to-value from their existing data lake investments.

Qlik Compose for Data Warehouses

Agile data warehouse automation

Speed time to analytics

Traditional methods of building and managing data warehouses are straining to keep pace with business demands. The multi-month, error-prone ETL development effort to set up a data warehouse – typically 60-80% of prep time – often means that the data model is out-of-date before the BI project even starts. Modifying these brittle data warehouses causes more delays, ties up skilled resources and delays project ROI.

To speed time to analytics, the data warehouse creation and management lifecycle must be streamlined wherever possible.

Agile Data Warehousing & Data Lake Pipeline Automation

Build a new data warehouse with Qlik Compose. Migrate an existing data warehouse to a new platform. Expand an existing data warehouse with new data feeds. Generate data marts for lines of business. Prototype, perform ad hoc analytics and testing.

Accelerate and simplify the loading and transformation of large-scale data lakes. Deliver data efficiently to any major Hadoop/Data Lake platform.

As the largest and highest-quality provider of change data capture technology for real-time incremental data replication, Qlik supports the broadest set of sources with the highest performance and lowest impact on production operations. Its technology has moved more than 80,000 databases to the cloud, and is widely recognized as the easiest data integration platform to manage given our 100% automated replication process.

Qlik has supplied innovative software solutions to its enterprise-class customers for nearly 20 years and has successful deployments at thousands of organisations worldwide.

Accelerate and simplify data warehouse or data lake design, development, testing, deployment and updates

Automated creation of analytics-ready data

Your Fastest Way to Analytics-Ready Data Lakes

Qlik Compose for Data Lakes automates the data pipeline to create analytics-ready data.  By automating data ingest, Spark/Hive schema creation, and continuous updates, organisations realise faster value from their data lakes.

Automatically generate the schema and structures in the Hive Catalog for Operational Data Stores (ODS) and Historical Data Stores (HDS) – with no manual coding.

As Compose incorporates Replicate’s CDC technology, you can be confident that your ODS and HDS accurately represents your source system whilst ensuring data consistency by leveraging the ACID MERGE operation, to efficiently process data insertions, updates and deletions while ensuring data integrity and avoiding user impact.

Business Benefits

  • Faster Data Lake operational readiness
  • Reduced development time
  • Reduced reliance on Hadoop skills
  • Standard SQL access for data architects

Business Benefits

  • Accelerate data warehousing projects
  • Reduce risk and ensure consistency
  • Improve business impact of analytics
  • Reduce time, cost and development requirements

Agile Data Warehouse Automation

A fresh approach to data warehouse automation

Qlik Compose automates the design, implementation and updates of data warehouses and data marts. It minimises manual, error-prone data warehouse design processes by automating data modelling, ETL generation and workflow.

Data architects can speed up analytics projects, optimise process and reduce risk. Compose flexibly supports either a model driven methodology, guided by business processes, or a data-driven methodology that is based on reporting requirements to easily adapt to new requirements or model changes through the data warehouse environment.

  • Reduce the time and cost of analytics projects on cloud platforms 
  • Quickly spin up, scale up, and iterate a data warehouse
  • Dynamically adjust data sources and models