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What Is Data Observability?

Data observability is the practice of monitoring and analyzing the health of an organization’s data and data systems. Essentially, it gives you a 360o overview of what’s happening with your data at any given point in time. This practice is beneficial, as it provides all stakeholders with an in-depth insight into how their data is collected, […]

Do You Have “Okta” for Your Data?

SaaS platforms exploded in the last few years for excellent reasons: scalability, cost, accessibility, and flexibility. But like any explosion, it left some messes in its wake. For IT and security teams, in particular, the increasing number of solutions in use created a seemingly never-ending need to add users, remove users, or change permissions every […]

The Machine Economy Is Here – The Digital Transformation Era Is Over

The age of digital transformation is over. It’s too late to be debating whether you should digitally transform your organization. The world has already digitally transformed. Everything is already digital-first, totally connected, in the cloud, and powered by data, everywhere, all the time.  Digital-first organizations won. Everyone else missed opportunities to innovate, made costly mistakes, and failed […]

The Trend Toward Emphasizing Data Minimization

With GDPR being the “shot heard ’round the world,” the digital industry, the regulators, and the courts have developed and readjusted the way in which we need to think about this revolutionary body of law. Through this experience, I’ve had a few flashback analogies to Y2K: Leading up to the event, it was a period […]

What Is Synthetic Data?

Synthetic data refers to any dataset that is generated artificially. Most datasets are generated based on research, use cases, or other activity. In the case of synthetically generated data, datasets are instead developed in a way that replicates real datasets, so that they can act as supporting information during model training or testing processes. Gartner predicts […]

Five Essential Data Architecture Principles

Data Architecture principles are a set of policies that govern the enterprise data framework with its operating rules for collecting, integrating, using, and managing data assets. The basic purpose of the Data Architecture principles is to keep the supportive data framework clean, consistent, and auditable. The overall enterprise Data Strategy is built around these principles. […]