Your 360ᴼ View of all Your Data
Today, many organizations are investing in the implementation of a conventional data fabric to solve their siloed data issues. Conventional data fabrics integrate data from multiple disparate sources to provide a consistent dataset for seamless accessibility to trusted data. This data fabric becomes the data foundation that provides the 360ᴼ view of their data.
Forming a data fabric is a noble effort but is very challenging since the source data systems are disparate. All conventional data fabrics are large data silos in that they do not directly share data with their data sources or with other data systems not derived from the data fabric. Conventional data fabrics are challenging to scale as the number of point-to-point data transformations increases exponentially as do the overall costs as more data sources are incorporated into the data fabric.
The Compatible Data Fabric has many advantages over conventional data fabrics. The Compatible Data Fabric is composed of modular compatible data systems designed to support plug-and-play functionality. The Compatible Data fabric is very agile and scalable, as it can grow without added data integration software or associated costs. Compatible Data Fabrics can be developed and maintained for a small fraction of a conventional data fabric's time, effort, and cost.
The Business Perspective
Never before has a business had such informational power at their fingertips. The Compatible Data Fabric provides a single source of consistent and trusted instantly available data. Within the data fabric, each compatible data system forms direct links with every other compatible data system. These data system links are the weave of your Compatible Data Fabric. All your data fits together like the pieces of a jigsaw puzzle, providing a 360ᴼ view of all your data.
The Compatible Data Fabric also supports all the functionality and power of a data warehouse. This embedded data warehouse functionality is an enormous advantage over the conventional data fabric that is merely a data source for constructing a data warehouse. Business intelligence and analytics are intrinsic to your Compatible Data Fabric.
The Technical Perspective
Maxxphase implements compatible data systems in a multi-dimensional form, where each Data Compatibility Standard supports a standardized hierarchy of its master data domain. Since compatible data systems are data integrated without data transformations, they are also directly interoperable. Each level of granularity for every Compatible Data Standard promotes direct data interoperability across compatible data systems. Each compatible data system becomes an integral component in a multi-tiered Compatible Data Fabric. The data weaves between compatible data systems are very comprehensive. As such, the Compatible Data Fabric formed from these data systems also directly supports multi-dimensional analytics.
Each compatible data system incorporates all data warehouse functionality, such as roll-ups and drill-downs, slicing, and dicing. You can dynamically blend various combinations of compatible data systems, forming a virtualized or a materialized business intelligence environment specific to an analytic need.
Traditional data fabrics tend to have several performance issues. In contrast, compatible data systems are very agile and support data retrieval performance enhancements. The direct data weaves of the Compatible Data Fabric are far more efficient than the indirect, transformed data weaves used in traditional data fabrics. Compatible data systems also support the materialization of aggregate data and consolidated data to eliminate inefficient data retrieval. Compatible Data Fabrics will easily outperform traditional data fabrics.
Compatible data systems fit together with data blending because the data in compatible data systems are integrated and there is extensive direct data interoperablity. The resulting Compatible Data Fabric has all the functionality of a traditional data fabric and a whole lot more. If you have an interest in data fabrics, you need to find out about Compatible Data Fabrics.