Understanding the Difference between Data Integration & Data Interoperability

0 February 28, 2018

Transformation-based data integration has nearly reached its capacity. Therefore, to meet the growing data needs of this century, businesses must adopt Universal dataset interoperability. With the transition from ETL-based data integration to universal dataset interoperability, companies will realize significant business advantages.

So what is data integration, and why must universal dataset interoperability replace it? In the article “Integration vs. Interoperability: What’s the difference and why should you care?” authored by Bobby Roberts, he contrasts two essential approaches for combining data from multiple information systems. The author contrasts data integration, which is commonly used today, with the more modern technology of dataset interoperability.

Leaving Behind Data Integration, Moving Toward Universal Dataset Interoperability

To be clear, data integration is defined by IBM as “the combination of technical and business processes used to combine data from disparate sources into meaningful and valuable information.” Organizations spend a fortune on tedious data integration projects to obtain the information they need to run their business.

While many in the IT industry have focused on improving data integration, few have asked the critical question: “Why are we building information systems to be disparate?” Every day, organizations create data systems without addressing the ability to share data directly across systems. With current information system design methods, every data system is disparate as designed and may be best characterized as an dataset silo.

Whenever data was needed from multiple disparate information systems, a form of data integration was used. As such, data integration became the offspring of these deficient disparate information systems. Now, information technology is about to change as we move from data integration methods to more efficient universal dataset interoperability.

Looking at Enforced Data Integrity

Maxxphase has developed a design-based solution for making disparate datasets universally interoperable. Using Data Compatibility Standards, Maxxphase standardizes master data representations in each dataset to resolve their master data conflicts and to enforce data integrity between the datasets. The result is a set of Universally Interoperable Datasets that spontaneously form a Modular Data Fabric with end-to-end data integrity enforcement.

Now that information systems are being designed to be compatible, they’re able to share their data directly. As defined by Bobby Roberts, “Interoperability is real-time data exchange between systems without middleware.” For our team at Maxxphase, universal dataset interoperability is achieved without middleware or data transformations, as suggested by Roberts. However, data need not be exchanged between Universally Interoperable Datasets. Instead, data is seamlessly shared, in place, with the data from any other Universally Interoperable Datasets.

The vision of Maxxphase Data Compatibility is a purely design-based solution that is the catalyst to moving information technology away from current integration methods and into the bright future of universal interoperability. The end of the data integration era is nearing. Thanks to Maxxphase Data Compatibility, businesses can create universal data interoperability throughout their organization, throughout an industry, and even across industries. With the transition to universal interoperability, organizations will be able to share unlimited business information and intelligence, finding unprecedented business agility, streamlined IT, strengthened strategic partnerships, and much more.

The real difference between data integration and universal data interoperability is simple — it’s Maxxphase. Contact us today to put universal data interoperability into action for your business.