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The Future of Data Integrity

TDE – Data Integrity means Value Creation

November 15, 2019

In our previous blog post, we presented the concept of trusted data exchange and what it means. With this blog post, we expand on the idea of trusted data exchange, how it can be established and how it creates value in a multitude of dimensions.

Establishing Trust between Parties

The necessity to establish trust between parties has always been a critical part of businesses. Most commonly trust is understood as the existence of uncertainty and hence uncertainty related risk. Here trust is a mechanism that either creates proof of integrity or shifts the ownership of the risk to a third party for compensation. Trust is a basis that needs to be established to an extent that the perceived value that could be gained outweighs the perceived risk. With the rise of digitalization, this has to be done cost-efficiently on a much greater scale, not only to facilitate business but create value too.

A middleman has been the most common facilitator and creator of trust between untrusted parties. Usually, it’s some kind of trusted institution or organization which involved parties agree upon. This type of solution is also applied for digital transactions, where a trusted third party supplies the environment to complete transactions upon.

The man-in-the-middle solution, however, has several drawbacks. It is usually very slow-paced – hence stifling business. Costs drastically increase with increasing data transactions. Lastly, the man in the middle needs to be trusted – creating dependency of involved parties to the trustworthiness of the organization in the middle. Even further, this means that outside of the agreeing parties the man-in-the-middle has no recognized authority, which means that he cannot be useful outside of their framework.

Drawbacks of the middleman:

  • Creates extra business step slowing business
  • Usually slow
  • Authority confined to an agreed space

Creating value from data curation

Data can gain value through different means; the simplest way is having more of it. With more data, the owner is more likely to draw correct conclusions from subsequent analysis based on the data. A second way to increase the value of data is by analyzing it. Analyzing data increases its value as the data now brings valuable insights for decision-making processes.

Lastly, neither the amassing nor the analysis of said data would produce any value if the data at hand cannot be trusted. If the data’s integrity cannot be sufficiently ensured, there will be a risk of incorrect conclusions. This not only means there is no value gained from amassing and analyzing data, but it also incurs a risk. The risk is that decisions made on false data, or falsely analyzed data create costs rather than value by supporting the wrong choice. Further, it creates a sunk cost of analyzing and amassing without integrity. Data integrity prevents negative impacts from tampered or illegitimately modified data.

Having the correct data is of high importance as analysis based on it, are used to predict consumer behavior. The results of the analysis may greatly impact mission-critical strategical decision of an organization. That is why the analysis of hard data usually trumps the individual opinion;

“If we have data, let’s look at data. If all we have are opinions, let’s go with mine.”
― Jim Barksdale CEO of Netscape

It must be noted however that data needs to be curated to gain such value. The first and most obvious type of curation is through analytics to gain valuable insights. But what if the underlying data is incorrect? What if someone tampered with it, falsifying any learnings taken from it, with possibly catastrophic effects on the organizations.

Data curation:

  • Increased amount of related data increases the value of analytics
  • Data analytics may result in valuable insights
  • Data integrity to ensure no nefarious or other changes have been made to the data

Going even further, organizations may decide to exchange data for data or for monetary compensation. Now it becomes imperative for the recipient to be able to trust the data received. Without assured data integrity, the recipient would not only accept data but also the implicated risk of falsehood and hence false analysis, lowering the perceived value of the exchanged data.

Read the entire whitepaper “Trusted Data Exchange – Business acceleration in the digital age” here.