Our co-founder, Robert Mack, has spent more than 25 years architecting various data integration solutions for some of the largest and most prestigious businesses in the world. He recognized the inefficiencies of established data integration methods and decided there just had to be a more efficient method to integrate data.
Our research led to the development of Standards-Based Data Integration, direct dataset interoperability, plug-and-play modular datasets, and the Compatible Data Fabric. There are currently seven issued patents for these Data Compatibility Methods dating back to 2009. Data Compatibility Methods create compatible data system datasets that seamlessly interact to provide all the integrated data and information needed to run and grow any business.
The Root Cause of the Data Integration Problem
The established data modeling methods are the root cause of the data integration problem. Data modeling methods developed in the 1970s, the age of mainframe computing, never attempted to design data systems that could work together. All data systems designed using established data modeling methods are incompatible or standalone data systems that are often characterized as data silos – isolated data systems best suited for mainframe computing of the 1970s. These standalone data systems are a huge hindrance to modern business practices.
Compatible Data Modeling
Once the root cause of the data integration problem was determined, a solution was engineered to fix these data modeling deficiencies. Our research uncovered which factors were critical to integrating data models as well as integrating the databases engineered from these data models.
Established data modeling methods were then augmented to focus upon the critical factors of data model integration. Now, two or more compatible data models can be seamlessly combined to form a larger compatible data model. For the first time ever, multiple independently-designed data models may be combined to form a larger compatible data model. Compatible data modeling was born!
When compatible data models are forward-engineered into databases, the resulting databases are also compatible. For the first time, multiple directly-interoperable data systems could be implemented! Each compatible data system becomes an integral component of the compatible business data environment where all data is directly integrated – integrated without data transformations.
Today, data compatibility is a success beyond all expectations, and we are excited to bring this game-changing innovation to healthcare, government entities and many more businesses and industries!
Data Compatibility Standards
The next challenge was to convert existing standalone data systems into compatible data systems. Since millions of standalone data systems already existed, a conversion method is needed in order for data compatibility to be a true success.
It became obvious that this conversion was only possible using a standards-based methodology. Maxxphase Data Compatibility Standards was therefore devised to support converting existing data systems into compatible data systems. With these standards, any data system could be made compatible with any other compatible data systems, including data systems from third parties. Beyond that, now, industry-specific Data Compatibility Standards can be devised to make data systems for an entire industry directly interoperable and automatically integrated. We at Maxxphase invite you to experience this whole new world of compatible data.