Data-driven decision making is a key competitive factor for modern businesses. Enterprises adopt Data as a Service to pool datasets from previously siloed data stores. This enables data provisioning, processing and compliance on one central data hub.
However, adopting Data as a Service and the added complexity of managing high data volume and variety comes with challenges such as maintaining privacy for datasets, data policy and compliance and increases the risk of malicious or accidental data breaches from internal actors.
When managing large data volumes, complexity in maintaining compliance and setting policies increases. Privitar tools help set consistent privacy policies across the data estate and introduce additional features such as watermarks which facilitate data lineage and audits.
Making data widely accessible across an organisation can increase risk of malicious or accidental data breaches by internal actors. In particular, in some cases anonymised data may be re-identified by linking seemingly anonymised datasets together. We introduced features such as Protected Data Domains that minimise the risk of such linkage attacks.
Data Workflow Architecture
Solution brief: Data Privacy as a Service
Reduce the time, cost and risk of provisioning valuable datasets.
Data as a Service (DaaS) - Challenges and Solutions
What are some of the challenges of adopting a Data as a Service (DaaS) approach, and how best to overcome them.
Data Privacy and Innovation for Telecoms
How can telecoms innovate with data whilst ensuring the privacy of their customers' sensitive information?
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