In today's information driven economy, data is a fundamental asset to most businesses. As more and more data moves to the cloud, getting information and insight to the right people and the right applications at the right time becomes progressively more difficult. With the introduction today of the Oracle Data Integrator Cloud, organisations can improve their agility by deploying projects more quickly, reduce risk with an open, non-proprietary technology, and reduce costs with better productivity.
"To be effective and agile, enterprises need seamless communication and flow of data between sources and targets - data originating from IoT, Web, and business applications or data that is stored in the Cloud or on premises", stated Jeff Pollock, vice president of product management, Oracle. "Oracle Data Integrator Cloud provides businesses with a high-performance, simple, and integrated Cloud service to execute data transformations where the data lies, with no hand coding required, and without having to copy data unnecessarily."
Easy to use and integrate, Oracle Data Integrator Cloud helps organisations improve productivity, reduce development costs, and lower total cost of ownership by facilitating better data movement and transformation between Oracle and non-Oracle systems, data sources, and applications. It offers a flow-based declarative user interface along with release management capabilities that allow customers to improve productivity and better manage their code, as well as their development, testing and production environments. Oracle Data Integrator Cloud's high performance architecture, with its E-LT capabilities and advanced parallelism options enable faster, more efficient loading and transformation for data marts, data warehouses, and Big Data systems.
Oracle Data Integrator Cloud is fully integrated with Oracle's PaaS offerings, including Oracle Database Cloud, Oracle Database Exadata Cloud, and Oracle Big Data Cloud. Oracle also delivers pre-built integration for non-Oracle solutions, allowing users to seamlessly switch between underlying Big Data technologies such as Hive, HDFS, HBase, and Sqoop.