Data sharing is a risky business – What’s the alternative?

Vinay Samuel Zetaris Data Fabric Founder CEO
Vinay Samuel
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When you consider the plight of Google, Facebook, the US government and many other large commercial and non-commercial enterprises who have been subject to data breaches from significant security attacks, one would have to concede that data sharing or putting your data in the hands of third parties is a risky business.

Gartner, a prominent industry analyst, penned a paper Why and how to measure the value of your information assets suggesting that information is a business asset to be managed, deployed and valued. Many organisations are driving towards the notion of data monetization and being able to recognise and value their business information. From this industry trend we have seen the growth of start-up businesses targeting the idea of a data marketplace where organizations can contribute their unique view of the market or industry derived from the transaction, clickstream or other customer behaviour data. The data they generate through their normal business practices.

The proposition behind data sharing is that one organization is willing to trust another organization in terms of taking, handling, protecting and marketing the others information assets. This may seem to be a viable proposition, particularly when the trusted party (for instance the “market place” organisation) is backed by large investors.

If one considers the state of the cyber security industry and the ever-swinging pendulum of capability between white hat and black hat hackers, it is becoming more apparent however, that the physical exchange of data may be, at best, an irresponsible practice. Especially when you consider what happens in the downside.

Will that trusted party's (who has your data) balance sheet protect you from massive potential financial downside risks?

So, if you are excited and motivated by the value of your data in terms of direct data monetization, what is the alternative?

What if you could share the insight your business has that others would be willing to pay real money for without physically giving the data away?

What if you could provide a virtual window into the patterns, segments, correlations and other pertinent information while setting governance and business rules on top of your data so that no one could either see private customer information nor have access to your precious business data and IP?

At Zetaris, we call this a Privacy Preserved Data Exchange, whereby no data is ever shared or given to another party; and any exchange of market-level insight is tightly governed by the party who ultimately owns the asset – all within their firewall.

We believe, and have seen in the market, that this is the only safe and responsible way by which organizations can comply with the complex and sophisticated privacy and consumer protection legislation that is prevalent or emerging in every western jurisdiction.

Zetaris has a fully documented reference architecture and data virtualization solution which enables owners of information assets to share high level insight without breaching data privacy and information governance policies and legislation.

The Zetaris Enterprise Data Fabric is the next-generation data platform whereby connections to source data is automatically made, a virtual unified view of all the data, no matter where the data resides, and a common data model is provided to the tools, dashboard and applications. A virtual data view, across the enterprise and over the internet, is created to access all the data for analytics, business applications and other information outcomes.

All of this is provided with in-built governance, policy and privacy rules that are applied when the data is queried in real-time ensuring true operational governance of enterprise data.

If you would like to access the benefits of data monetization through sharing, don't physically give your data away. Use the privacy preserved data exchange approach and solution from Zetaris and only share industry level insights.

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