Self-service Analytics

Self-service Analytics:

A data provisioning system that lets a large number of data users in an organization access data for analytics, without needing to request access from IT for every query. This includes non-traditional data users, e.g. from the line of business, or so-called "citizen analysts". It's a huge step for organizations trying to break down data silos and derive value, insight, and competitive advantage from their data.

Such a central repository that includes rich and sensitive business data (e.g. on customers, transactions, financial performance) is highly vulnerable to privacy attacks. For an effective self-service analytics system to operate privacy-safely and at scale, its in-built data protection mechanisms need to be centrally managed and apply consistent privacy policies across all data. Also referred to as "Data-as-a-Service".

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Data de-identification 101 Webinar

Data as a Service (DaaS) - Challenges and Solutions

Here you can find a short video interview with David Roberts, Technical Sales at Privitar, in which he talks about some of the challenges of adopting a Data as a Service (DaaS) approach, and how best to overcome them.

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