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Welcome to All Things Data Integration: Announcements, Insights, Best Practices, Tips & Tricks, and Trend Related...

  • June 29, 2020

New: Oracle Cloud Infrastructure Data Integration

Steve Quan
SR. PRINCIPAL DIRECTOR, PRODUCT MARKETING

What Is Oracle Cloud Infrastructure Data Integration?

These days, you often hear people talk about how their company tries to gain a competitive advantage by being data-driven.  They are all trying to keep their company relevant in today’s world using data and technology.  They want to use data to engage with customers through digital channels to share information, make transactions, and provide support.  When customers decide to buy something from their mobile devices, the company’s operational systems need all the necessary information to execute and complete the transaction.  If a customer calls about a problem, support needs the most current data about the person to provide the best service possible.

Being data-driven requires organizations to access all available data and convert it so that analytical apps understand the information.  Data engineers and developers have to wrangle data into a useful format quickly for organizations to make informative decisions. This requires easy-to-use user interface that can prepare and ingest data into data lakes and decision science applications.  Data Engineers can’t wait for DBAs to help write integration code or modify database tables with new columns to add meaningful information.

 

Oracle Cloud Infrastructure Data Integration is a cloud native, serverless ETL (extract, load, transform) service on the Oracle Cloud.  This simplifies integration within the Oracle Cloud Infrastructure eco-system.  It ingests and manipulates large volumes of structured and unstructured data faster into Oracle cloud autonomous databases, as well as data lakes.

A new intuitive, no-code, graphical user interface simplifies all of this. Data engineers can easily design the data flow to discover and connect sources and targets.  They can build data flows and rules to convert information into a meaningful format.  It automatically validates connections and handles schema drift to ensure that database sources and targets are connected and the integration flow code is designed correctly. With an easy-to-use user interface, organizations can complete integration projects more quickly with the assurance that the process is correct and runs resiliently.    

 

Why Do We Need Oracle Cloud Infrastructure Data Integration?

When organizations want to become more data-driven, they need to gather, convert and store data into useful formats. Some of the data is transactional from operating systems and some is unstructured customer data from hundreds of Big Data sources. You’ll need to discover and connect many databases, then extract, map, transform and move it to the right places.  As data volumes grow, information needs to be loaded efficiently into target systems.

The job of extracting and transforming data is often done by developers writing code manually.  Imagine having to manually maintain and update the integration code every time a schema or API changes. Today, it is all about speed because the competition is just a click away.  If your product catalog shows old or incorrect information and prices, customers will find other storefronts.  When support can’t find the cause of a problematic transaction, customers become frustrated and your goodwill suffers.

 

Simplify Data Capture

For the past two dozen years, organizations have been building data marts and data warehouses to analyze relational data coming from operational systems.  These systems are pre-defined to answer specific questions like “sales by region.”  The information is structured for fast queries from historical, transactional data.  They were designed for reporting and analysis.

Oracle Cloud Infrastructure Data Integration is designed with a graphical, no-code user interface that guides you through building the integration code. Also, you get the benefits from being able to:  

  • Validate the data flow to make sure all the nodes are connected and configured properly and integration logic is written correctly.
  • Visually preview results of the transformation at any time to see if the joins and merges are done correctly to give meaningful results. You don’t have to run the entire integration project to see how the design is working.
  • Make changes on-the-fly until it’s perfect.
  • Be confident that an optimizer automatically generates the most efficient executable code for more resilient data transfer.