The Future of Data

There are three "truths" that, together, demand a new approach to the way we store, secure, manage and access data.

We are engaged in a never-ending, exhausting and expensive war to keep cyber criminals out of our data. Do we really get the ROI on our cybersecurity investments that we should?

We have masses of unused data storage capacity across billions of devices across the globe… and yet we continue to build new data centers.

The proliferation of AI and LLM's has highlighted critical data questions that go beyond security and privacy. We now need to worry about data integrity - including data provenance, data ownership, data rights and rights enforcement.

Our current approach of centralized data storage made sense when almost all processing power existed in mainframes. The processing power landscape has changed and we live in a world of desktops, laptops, smartphones, and IoT devices. Yet our data storage remains the same. We transport our data to centralized locations and surround what is essentially "dumb" data with cumbersome, costly infrastructure so we can organize, secure and make sense of the data.

We must think differently. The way to solve these data challenges is to store our data across the billions of available devices and we need to attach intelligence, security and control to the data itself. Imagine a data management system that knew where every record was stored across each of billions of devices. Imagine a contract document that could be found directly by query, without tables and hierarchies. Imagine that document retained an immutable history of everything that happened to it before, during and after its creation. Imagine that contract being accessible only to those authorized to see it and that access control could be managed down to location, time, device, quantity and use. Imagine that contract being available in the format required. by any other system , without point to point translations.

This must be the way forward for economic, safety and environmental reasons. We need to reverse decades of top-down data management of "dumb" data. We need a bottoms-up approach where each individual data record is backed up, self-aware, secured, controlled, directly findable and stored where it needs to be.

PrivacyChain is the Distributed Data Management System that enables this vision, PrivacyChain is the future of data - now.

Centralized v Decentralized Data Management

Web3 – or the Distributed Internet

Dumb data v Smart Data

Data Security = Data Provenance and Integrity

Data Security

Centralized data management, storage and security models date back to the days of mainframes. When processing power was centralized, it made sense for data to be stored centrally. Now that centralized processing world has been turned on its head. Apple ships more processing power in an hour, on iPhones alone, than the processing power delivered by the world’s biggest supercomputers. We have an “inverted cloud” where the bulk of processing power and storage capacity is distributed across billions of devices. Centralized data storage adds a level of “remoteness” and inefficiency to decentralized processing.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

PrivacyChain knows where every record is stored (using what we call “Secure DNS for data), which means that the DDMS will locate the record closest to the source of a query, minimizing length and complexity of routing.

In the context of individual data storage, PrivacyChain will seek to store data on the individual’s own devices for easy access, with clones stored elsewhere across the ecosystem of available devices.

Similarly in the enterprise environment, a financial employee would have the data they most often use on their devices. Every time the employee makes an authorized change, their copy of the file synchs with its clones and, if the clones validate the change as legitimate, all clones update themselves.

Centralized v Decentralized Data Management

Dumb data v Smart Data

Web3 – or the Distributed Internet

Data Security = Data Provenance and Integrity

Data Security

Centralized data management, storage and security models date back to the days of mainframes. When processing power was centralized, it made sense for data to be stored centrally. Now that centralized processing world has been turned on its head. Apple ships more processing power in an hour, on iPhones alone, than the processing power delivered by the world’s biggest supercomputers. We have an “inverted cloud” where the bulk of processing power and storage capacity is distributed across billions of devices. Centralized data storage adds a level of “remoteness” and inefficiency to decentralized processing.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

PrivacyChain knows where every record is stored (using what we call “Secure DNS for data), which means that the DDMS will locate the record closest to the source of a query, minimizing length and complexity of routing.

In the context of individual data storage, PrivacyChain will seek to store data on the individual’s own devices for easy access, with clones stored elsewhere across the ecosystem of available devices.

Similarly in the enterprise environment, a financial employee would have the data they most often use on their devices. Every time the employee makes an authorized change, their copy of the file synchs with its clones and, if the clones validate the change as legitimate, all clones update themselves.

Centralized v Decentralized Data Management

Dumb data v Smart Data

Web3 – or the Distributed Internet

Data Security = Data Provenance and Integrity

Data Security

Centralized data management, storage and security models date back to the days of mainframes. When processing power was centralized, it made sense for data to be stored centrally. Now that centralized processing world has been turned on its head. Apple ships more processing power in an hour, on iPhones alone, than the processing power delivered by the world’s biggest supercomputers. We have an “inverted cloud” where the bulk of processing power and storage capacity is distributed across billions of devices. Centralized data storage adds a level of “remoteness” and inefficiency to decentralized processing.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

PrivacyChain knows where every record is stored (using what we call “Secure DNS for data), which means that the DDMS will locate the record closest to the source of a query, minimizing length and complexity of routing.

In the context of individual data storage, PrivacyChain will seek to store data on the individual’s own devices for easy access, with clones stored elsewhere across the ecosystem of available devices.

Similarly in the enterprise environment, a financial employee would have the data they most often use on their devices. Every time the employee makes an authorized change, their copy of the file synchs with its clones and, if the clones validate the change as legitimate, all clones update themselves.

Centralized v Decentralized Data Management

Web3 – or the Distributed Internet

Dumb data v Smart Data

Data Security = Data Provenance and Integrity

Data Security

Centralized data management, storage and security models date back to the days of mainframes. When processing power was centralized, it made sense for data to be stored centrally. Now that centralized processing world has been turned on its head. Apple ships more processing power in an hour, on iPhones alone, than the processing power delivered by the world’s biggest supercomputers. We have an “inverted cloud” where the bulk of processing power and storage capacity is distributed across billions of devices. Centralized data storage adds a level of “remoteness” and inefficiency to decentralized processing.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

Local processing of locally stored data offers major performance improvements and savings. PrivacyChain stores data where it is needed across the ecosystem of available devices. PrivacyChain can dynamically manage the location of data based upon demand. Each record can be cloned and clones regularly synch with one another which means that clones can be distributed for local access and remain identical.

PrivacyChain knows where every record is stored (using what we call “Secure DNS for data), which means that the DDMS will locate the record closest to the source of a query, minimizing length and complexity of routing.

In the context of individual data storage, PrivacyChain will seek to store data on the individual’s own devices for easy access, with clones stored elsewhere across the ecosystem of available devices.

Similarly in the enterprise environment, a financial employee would have the data they most often use on their devices. Every time the employee makes an authorized change, their copy of the file synchs with its clones and, if the clones validate the change as legitimate, all clones update themselves.

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The Future of Data

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Copyright@2023 Privacy Chain LLC. All Rights Reserved

PrivacyChain

DDMS

Data Security

Secure Office

Use Cases

The Future of Data

About Us

Copyright@2023 Privacy Chain LLC.

All Rights Reserved

PrivacyChain

DDMS

Data Security

Secure Office

Use Cases

The Future of Data

About Us

Copyright@2023 Privacy Chain LLC.

All Rights Reserved

DDMS

Data Security

Use Cases

The Future of Data

About Us

DDMS

Data Security

Use Cases

The Future of Data

About Us

DDMS

Data Security

Use Cases

The Future of Data

About Us