Necessity is the Mother of Invention!

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 investigation into the data integration problem led to the conclusion that conventional data modeling methods were deficient in that they always produced disparate or siloed datasets. This dataset design deficiency was relatively easy to correct, so we created Compatible Data Modeling. Compatible Data modeling designs and implements compatible datasets that may be seamlessly combined on demand to collectively function in a manner indistinguishable from a single large consistent dataset.

Our work with data compatibility led to the development and patenting of Dynamic Data Integration, direct dataset interoperability, plug-and-play modular datasets, and the Compatible Data Fabric. Most importantly, expensive and time-consuming data integration projects, data warehouse projects, and data fabric initiatives are no longer needed in any data architecture since that functionality is delivered by Compatible Datasets. Operational decision support, analytics, business intelligence, and the like, all become much more productive and trusted when your datasets are compatible. Data Compatibility Methods create compatible 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 datasets that could work together. All datasets designed using established data modeling methods are incompatible or standalone datasets that are often characterized as data silos – isolated datasets best suited for mainframe computing of the 1970s. These standalone datasets 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 on 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 datasets could be implemented!  Each compatible dataset 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 enrich existing standalone datasets into directly interoperable compatible datasets. Since millions of standalone datasets already existed, a dataset enrichment method was 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 were therefore devised to support enriching existing datasets noninvasively to become compatible datasets. With these standards, any dataset could be made compatible with any other compatible datasets, including datasets from third parties. Beyond that, now, industry-specific Data Compatibility Standards can be devised to make datasets for an entire industry directly interoperable and automatically integrated. We at Maxxphase invite you to experience this whole new world of compatible data.