Standardized Data Containers

0 August 21, 2024

In a recent website post The Five S’s of Nextdata, Zhamak Dehghani discussed data product containerization. Aspirationally, Zhamak states “Data product containers are the standard for building, sharing, and managing … data products across a large mesh.” She goes on to propose that “These standards ensure interoperability, consistency, and ease of integration across diverse platforms, making it easier for organizations to adopt data mesh without running into costly interoperability challenges.”  In reality, dataset containers are more full-featured than Zhamak anticipated.

Maxxphase Provides the First Standardized Dataset Containers

Maxxphase is the industry leader in Data Compatibility having been issued nine patents for our Data Compatibility Standards products. Our Data Compatibility Standards can be noninvasively applied to any dataset to encapsulate or containerize the dataset. This containerization includes the data mesh datasets of any mesh data products. The enriched compatible dataset becomes modular plug-and-play with universal direct dataset interoperability. Direct dataset interoperability allows data from multiple datasets to be seamlessly combined or blended on demand. Because of their universal direct interoperability, these modular datasets spontaneously form an analytics-ready data fabric. In addition, compatible datasets have comprehensive referential data integrity enforced between them enriching and improving the overall data quality of your datasets.

Standardized Dataset Containers

Any dataset’s data context or data container is essential as the identifier of dataset significance relative to other datasets. Unfortunately, predominant data administrative methods provide disparate data contexts, which confuses the significance of datasets relative to each other and leaves your data architecture disjointed. Maxxphase Data Compatibility Standards provide a solid container of data context that uniquely identifies the significance of any dataset. These standardized data contexts improve data quality while defragmenting your data architecture.

The data context of a dataset also defines the functionality of the dataset. For example, the Maxxphase Data Compatibility Standards provide direct dataset interoperability among any standardized datasets. Any data from a compatible dataset can be seamlessly combined or blended with the data from other compatible datasets on demand. Our Data Compatibility Standards are also dimensional imparting each dataset with the functionality of a compatible data warehouse. Maxxphase Data Compatibility provides enhanced data administration methods far superior to traditional data administration methods.

Data Compatibility Reduces Data Architecture Complexity while Improving Business Agility

Maxxphase Data Compatibility Standards form reusable dataset containers that anchor each dataset to a common foundation. This anchored foundation provides all the dataset functionality required to support operational as well as analytical data needs. Our Data Compatibility Standards greatly reduce data architecture complexity and cost by eliminating the need for future data integration efforts. Complex data pipelines and data transformation software are no longer needed as traditional data integration is replaced by more efficient and agile direct dataset interoperability.

All five S’s as defined by Zhamak, in her article, are met in that compatible datasets are Standardized, Simple to implement, Seamless in use, Small  as in decentralized, and have a Significant impact for your business. Please contact us at Maxxphase for more information.