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  • August 6, 2018

Data Integration Platform Cloud (DIPC) 18.3.3 is available!

Sandrine Riley
Product Management, Oracle Cloud Infrastructure - Data & AI Services

Data Integration Platform Cloud (DIPC) 18.3.3 is now available!

Do you know what DIPC is?  Check out this short 2 minute video!


DIPC is innovative!  With an Elevated Task driven approach that guides users through their Data Integration journey, DIPC seeks to simplify and revolutionize Data Integration!  The Elevated Task is a simple, pre-defined set of steps to assist in creating a specific and useful, common job within Data Integration.  These tasks result in simpler solutions such as data migrations or data warehouse/data lake automation and projects that are delivered more quickly, but yet, well designed and effective.

Let’s cover some of the brand new and exciting features and tasks in this release! 



This release helps with data lake automation, enabling an intuitive instantiation and copy of data into a data lake, in an effort to help reduce some of the existing data engineer/ data scientist friction through a new Data Lake Builder task!  You can quickly create a comprehensive, end-to-end repeatable data pipeline to your data lake.  And – note that nothing is moved to data lake without being fully governed! 



The Replicate Data Task helps address high availability.  Replicate into Oracle… or Kafka!  And, bring that together with Stream Analytics whereby event process is made possible on real-time data streams, including Spatial, Machine Learning, queries on the data stream or cubes.  With Stream Analytics, you can analyze complex event data streams that DIPC consumes using sophisticated correlation patterns, enrichment, and machine learning to provide insights and real-time business decisions.

Additionally, you have already heard us mention the Synchronize Data Task, the Data Preparation Task, the ODI Execution Task, but this release features enhancements to many of these!

For a quick recap:


  • Synchronize Data:  The Synchronize Data task enables you to copy your selected data from a source to target, and then keeps both databases in sync. You can also use filter rules to include or exclude specific data entities in your job. Any change in the source schema is captured and replicated in the target and vice versa. After you create a synchronize data task and set it up to synchronize all data or specific data entities, you can run the job. If you setup policies for your job, you'll receive notifications for your specified criteria. For more information, see Creating a Synchronize Data Task.

  • Data Preparation:  The Data Preparation task enables you to harvest data from a source File or Oracle database Connection, and then cleanse, organize, and consolidate that data, saving it to a target Oracle database. For more information, see Setting up a Data Preparation Task.



This release also provides updated components under the covers such as:  Enterprise Data Quality, Oracle Data Integrator, GoldenGate for Oracle 11g/12c, GoldenGate for Big Data, and GoldenGate for MySQL  Oracle Stream Analytics is part of DIPC as well, and is available only for user-managed Data Integration Platform Cloud instances.


Want to learn more?  Visit the DIPC site and check out some of our archived webcasts HERE!


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