Thursday Apr 11, 2013

Why Real Time?

Continuing on the five key data integration requirements topic, this time we focus on real-time data for decision making. 

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Wednesday Mar 27, 2013

On Premise and Cloud

Follow-on blog about five key data integration requirements topic, which focuses on data integration for cloud architectures. 

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Friday Mar 15, 2013

Pervasive Access to Any Data

In my previous blog, I shared with you the five key data integration requirements, which can be summarized as: integrating any data from any source, stored on premise or in the cloud, with maximum performance and availability, to achieve 24/7 access to timely and trusted information. Today, I want to focus on the requirement for integrating “any data”.

We all feel the impact of huge growth in the amount of raw data collected on a daily basis. And big data is a popular topic of information technology these days. Highly complex, large volumes of data bring opportunities and challenges to IT and business audiences. The opportunities, as discussed in McKinsey’s report, are vast, and companies are ready to tap into big data to differentiate and innovate in today’s competitive world.

One of the key challenges of big data is managing the unstructured data, which is estimated to be %80 of enterprise data. Structured and unstructured data must coexist and be used in conjunction with each other in order to gain maximum insight. This means, organizations must collect, organize, and analyze data from sensors, conversations, e-commerce websites, social networks, and many other sources.

Big data also changes the perspective into information management. It changes the question from “How do you look at your data?” to “How do you look at the data that is relevant to you?” This shift in perspective has huge implications in terms of information-management best practices and technologies applied. Data integration technologies now need to support unstructured and semi-structured data, in addition to structured transactional data, to be able to support a complete picture of the enterprise that will drive higher efficiencies, productivity and innovation.

Oracle addresses big data requirements with a complete solution.

In addition to Oracle Big Data Appliance for acquiring and organizing big data, Oracle offers Oracle Big Data Connectors that enable an integrated data set for analysis. Big Data Connectors is a software suite that integrates big data across the enterprise. Oracle Data Integrator offers an Application Adapter for Hadoop, which is part of the Big Data Connectors, and allows organizations to build Hadoop metadata within Oracle Data Integrator, load data into Hadoop, transform data within Hadoop, and load data directly into Oracle Database using Oracle Loader for Hadoop. Oracle Data Integrator has the necessary capabilities for integrating structured, semi-structured, and unstructured data to support organizations with transforming any type of data into real value.

If you would like to learn more about how to use Oracle’s data integration offering for your big data initiatives take a look at our resources on Bridging the Big Data Divide with Oracle Data Integration.

Thursday Mar 07, 2013

5 New Data Integration Requirements for Today’s Data-Driven Organizations

How are the latest technology trends affecting data integration requirements? Read about the 5 key data integration requirements and Oracle's Data Integration product strategy in meeting these requirements.[Read More]
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Learn the latest trends, use cases, product updates, and customer success examples for Oracle's data integration products-- including Oracle Data Integrator, Oracle GoldenGate and Oracle Enterprise Data Quality

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