Traditional data system design and analysis methods are from the age of mainframe computing – methods that are absolutely ancient compared to 21st-century computing capabilities. Modern businesses need compatible data systems designed for today and beyond.
Compatible data systems begin with compatible data models
World-class businesses who want a competitive advantage should model their entire data universe. This data universe includes the organization’s data, as well as external data sources and targets, all of which may be included in compatible data models. Compatible data modeling produces integrated, compatible data models which fit together just like jigsaw puzzle pieces.
Traditional data modeling methods prevent an effective documentation process because these methods yield incompatible data models. Incompatible data models are unable to interact with one another, creating significant barriers to modeling an organization's entire data universe. Traditional data models may best be characterized as isolated data silo models. Traditional data models instantiate traditional data systems that are incompatible and conflicted data systems.
Compatible data models that contain Maxxphase Data Compatibility Standards solve this problem by creating compatible data models so businesses can accurately and completely depict their data universe, creating the most informed businesses and putting these organizations at a truly competitive advantage.
Compatible data modeling represents a giant leap forward in data science and in designing flexible, business-friendly data systems.
Businesses need collaborative data systems where all data and information is:
- Directly accessible
Data compatibility solutions from Maxxphase have updated the traditional data modeling methods by adding a focus upon developing compatible data models. These models support data system interoperability so that different data systems fit together like the pieces of a jigsaw puzzle, depicting an entire compatible data architecture for your organization. They also fit together with compatible data models from other organizations as needed.
These directly-interoperable compatible data models are used to instantiate compatible data systems and collaborate with any other compatible data systems. Traditional data models are far more limited, instantiating incompatible data systems that are best characterized as data silos. These incompatible data systems act in isolation, which prevents businesses from leveraging that competitive advantage they need to compete. It’s apparent that compatible data modeling methods should be favored over traditional data modeling simply because this outdated traditional technology is a detriment to the current business world.
Your Compatible Data Universe
Heavy investment in data warehouses and business intelligence programs demonstrate just how reliant the modern business is on data, information and knowledge to remain competitive. Yet, prior to data compatibility methods developed by Maxxphase, there were no standards for designing and managing the direct interactions between data systems. These data interactions across data systems are just as important as the data from the individual data systems, yet these interactions were ignored in the traditional design phase.
With Maxxphase Data Compatibility Standards, the future of business is much brighter. Data compatibility methods are used to network data sources, providing a consistent, interoperable environment where data systems can easily communicate with one another. From the business point of view, all data and information is trusted and completely accessible from the lowest level business transactions to the highest-level data on the CEO dashboard. This includes data across the entire organization, as well as data external to the organization across the entire industry.
All of our competitors collectively cannot approach this comprehensive compatible data universe as their offerings are for isolated incompatible data systems. Data compatibility is the only approach that can create this sort of cohesive data environment, allowing for total interoperability between all data systems. In a business environment founded upon the power of data, and in a marketplace that rewards nimble adaptability, total interoperability spells success.