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Maxxphase Data Compatibility is bridging the divide between Data Proliferation and Data Integration

0 May 3, 2018

The Problem

The world of data is growing and growing rapidly. According to Forbes “data volumes are exploding. More data has been created in the past two years than in the entire previous history of the human race”. This volume of data and information has greatly outpaced the technology responsible for making that data accessible and relevant to those that need it. Established data integration methods are used to overcome the barriers to access, to consolidate data, and to make the data relevant to their business needs. Established data integration methods are too slow, too expensive, and just woefully inadequate to meet the needs of modern business. Something totally new and innovative is required. That new innovation is Maxxphase Data Compatibility.

Why it Matters

Forbes reports “Estimates suggest that by better integrating big data, healthcare could save as much as $300 billion a year — that’s equal to reducing costs by $1000 a year for every man, woman, and child.” This is only scratching the surface of the savings Maxxphase can bring to the world of data. Businesses from all sectors, all industries, are burdened by the massive amount of data and information they rely on to operate their businesses. The world of data has become massive, and the demand for that data equally so, but no one has ever built a system to handle the mass production of data, until now.

How we fix it

Forbes also reports that “For a typical Fortune 1000 company, just a 10% increase in data accessibility will result in more than $65 million additional net income”. Today’s data systems are all data silos since they do not have external data access paths or designed links that directly and dynamically connect to other data systems. Whenever data is needed from two or more of these isolated data sources, hand-crafted data transformation software is required. These software-based data integration projects take far too long, cost far too much and fail far too often. Now that the data volume is growing dramatically, IT departments are struggling more than ever to keep up.

Maxxphase Data Compatibility Standards use an entirely different approach by simply making data systems compatible and directly interoperable with any other compatible data systems. These Data Compatibility Standards are a design-based solution that does not require data transformation software or data movement. These Data Compatibility Standards simply enhance the functionality of any data systems providing direct data access paths for dynamically connecting any of these compatible data systems as needed. Each compatible data system becomes an integral component of a virtual database and all the data of these data systems are simply shared in-place to be combined with any other data as needed.

Data compatibility improves data accessibility immensely. These data access paths are direct – no middleware or data transformations needed. These access paths are also dynamic – the data access paths may change with every new query. With compatible data systems, data access paths are built in and data accessibility across data systems is no longer a problem.

A compatible data environment is a game-charger for any business when compared to established data environments that are all based upon stand-alone data systems that require data transformations and data movement for data integration. Data compatibility saves a lot of work, slashes costs, and provides a vastly superior solution compared to traditional data integration methods.

All data should be compatible from the time it is created and remain compatible throughout its lifecycle. This compatible data may then be efficiently used directly with any other compatible data. So, there is no adverse effect as the volume of data increases because it does not increase the data handling effort. Also, the direct data interoperability provided by the use of Maxxphase Data Compatibility Standards provides access to any compatible data within the security constraints of the data systems of course.

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