Data Lake ROI: 5 Principles for Managing Data Lake Pipeline

IT departments face serious data integration hurdles when adopting and managing a Hadoop-based data lake. Consolidating data in bulk or real-time from hundreds or thousands of sources creates management complexity and source production impact. Many organizations lack the ETL and Hadoop coding skills required to replicate data across these large environments.

Qlik provides automated data lake pipelines that accelerate and streamline your data lake ingestion efforts, enabling IT to deliver more data, ready for agile analytics, to the business. Read this whitepaper to learn more about the following capabilities and more:

• Universal and hybrid data integration, with support for all major source and target platforms, both on premises and in the cloud

• Real-time integration, with zero-footprint change data capture technology that copies live source transactions with no production impact

• Efficient structuring processes that automate the creation and continuous loading of SQL-based Hive operational and historical data stores

• Scalability, with centralize, graphical management and monitoring of replication tasks across the environment