Our Universally Interoperable Datasets are Modular

0 December 31, 2024

What Are Modular Datasets?

Can you imagine a world where datasets seamlessly connect like Lego Blocks? Imagine forming a consistent data architecture without the usual data integration headaches. Our modular datasets are universally interoperable and ‘snap together’ dynamically, seamlessly joining and unifying data. You can combine these Universally Interoperable Datasets on demand, thanks to the Data Compatibility Standards that encapsulate and modularize each dataset. Much like a Lego Brick, we designed Universally Interoperable Datasets so you can connect them as needed.

Siloed Datasets vs. Universally Interoperable Datasets(UIDs)

There are currently two types of structured dataset access for digital data. First, there is the disparate siloed dataset, which has been in use since the dawn of digital computing. Everyone recognizes data silos as a hindrance to IT and business; it was the default access type since no other dataset access type was available. Recently, Maxxphase introduced their patented UIDs. The main difference is that UIDs have data integrity enforced among them, while siloed datasets do not. UIDs spontaneously join to form a Modular Data Fabric, while siloed datasets can not. This Modular Data Fabric collectively functions in a manner indistinguishable from a single consistent dataset. Fortunately, you can simply and noninvasively enrich existing siloed datasets to be UIDs.

Dataset Modularity

We modularize a dataset by encapsulating that dataset within a select group of Data Compatibility Standards (DCS). Each DCS is designed for a specific master data domain, providing master data and metadata commonality along with select dataset functionalities to be reused in each UID. You can modularize any existing dataset by enriching that dataset with the appropriate group of DCSs. This dataset enrichment delivers a standardized dataset interface that supports universal dataset interoperability.

Plug-and-Play Dataset Functionality

At Maxxphase, we specifically designed each DCS to be universally interoperable with the same DCS in any other UIDs. Since data integrity is enforced between DCSs, plug-and-play dataset functionality is inherited between UIDs. Much like joining database tables within a dataset, now, database tables can be reliably joined across multiple UIDs. Because each reusable DCS is multifaceted, and the DCSs encapsulates an entire datasets, your options for joining and unifying UIDs are numerous. Dynamic plug-and-play joins form and dissolve as needed among the UIDs. You can adapt UIDs on the fly to reshape the Modular Data Fabric to dynamically fit any dataset requirements as needed.

Analytics-Ready Power

We design each DCS in our universal dataset gateways to be dimensional. Therefore, each compatible dataset exhibits data warehouse functionality. This dimensionality, combined with multifaceted direct dataset interoperability, delivers a data warehouse foundation upon which more BI-related compatible datasets can be materialized. These modular datasets are analytics-ready out of the box. You can get analytics reports up and running quickly by removing the need for lengthy data integration/consolidation efforts. With our modular plug-and-play functionality, you can quickly add new datasets to a modular data fabric.

Advanced Data Fabrics

Compatible datasets spontaneously combine to form a data fabric type of data architecture. However, with direct dataset interoperability, we have delivered more advanced data fabric architectures. While the data fabric factory approach can produce a single monolithic data fabric, compatible datasets spontaneously form distributed data fabrics. These advanced data fabrics begin as distributed or federated, become modular plug-and-play, and even progress to include specific modular datasets such as customer 360 or product 360 datasets.

The creation of DCSs has led to our development of the first-ever modular plug-and-play datasets. These new datasets are low maintenance, dynamic, and agile while having the functionality of a data warehouse without needing to undergo costly and complex data integration efforts. Want to empower your datasets to become modular plug-and-play analytics-ready datasets? Reach out today!