Talend and Cloudera Navigator integration enhances data governance on Hadoop and Spark

Cloudera Navigator

Talend Big Data Integrator now supports Cloudera Navigator, enabling enterprises to gain end-to-end data governance on Apache Hadoop, maintaining mission-critical data integrity in the face of both rising data volumes and increasingly widespread access to that data.

The integration, announced by big data software integration provider Talend, enables a detailed level of data governance that includes both field-level data lineage and impact analysis.

“Companies face many trust and compliance challenges as they collect and connect greater data volumes and provide data access to more individuals throughout the organisation,” said Tim Stevens, vice president, corporate and business development, Cloudera, explaining why the granular level of detail provided by the new integration is increasingly important to enterprise customers.

“This is why Talend Big Data Integration and Cloudera Navigator make a strong combination, enabling the fine-grained data governance necessary for turning data into a trusted source that helps precisely track data movement, transformation, mapping and filtering,” he said.

The integration enables companies to monitor, audit and understand data access on Hadoop in the same way they do on traditional data warehouses, without compromising agility.

Cloudera Navigator customers are expected to gain greater insights through a holistic view of their data in Hadoop and to benefit from Talend’s ability to combine Spark, Spark Streaming and Machine Learning for integration.

“Hadoop is rapidly entering a phase of mainstream adoption that requires the type of comprehensive, enterprise-class data governance and control that Cloudera Navigator and Talend can provide,” said Ciaran Dynes, vice president of products, Talend.

“Together, we’re meeting the needs of the most stringent governance requirements by showing not only what happened at the data input and output level, but also at a very granular level of detail, including joins, filters and maps, right down to the field level of the data,” he said.