Matches in SemOpenAlex for { <https://semopenalex.org/work/W3089402258> ?p ?o ?g. }
Showing items 1 to 68 of
68
with 100 items per page.
- W3089402258 abstract "Adhering to internationally accepted data privacy principles in every new data analytics initiative ensures compliance with virtually all current government or industry-mandated data privacy regulations and enables the business to extract maximum financial benefit from available data assets without violating the trust between the organization and its customers. Privacy by design is a fundamentally important approach to achieving compliance with GDPR, HIPAA, and other data privacy or data protection regulations. This paper outlines how organizations can save time and money while improving data security and regulatory compliance and dramatically reduce the risk of a data breach or expensive penalties for noncompliance. What privacy by design means? Why it’s so important? and how to implement it within any organization, using data protection and data access control technologies. Build it in from the beginning to facilitate better regulatory compliance, reduce risk, reduce operating costs, shorten development times, improve customer trust and loyalty, and gain more open access to sensitive and regulated data for business benefit—without violating generally accepted privacy principles. The big change is Big Data. All the more explicitly, how organizations will use Big Data analytics to boost these developing data resources – driven by their profound enthusiasm to augment their assets and better contend in the market. While organizations have down to earth motivations to take advantage of their consistently developing perception space, they additionally have a squeezing need to implant in these frameworks improved security assurances. We outline in this paper just such an example – how an advanced Big Data sensemaking technology was, from the ground up, engineered with privacy-enhancing features. Some of these features are so critical to accuracy that the team decided they should be mandatory – so deeply baked-in they cannot be turned off. This paper demonstrates how privacy and responsibility can be advanced in this new age of Big Data analytics." @default.
- W3089402258 created "2020-10-08" @default.
- W3089402258 creator A5028627559 @default.
- W3089402258 creator A5030817278 @default.
- W3089402258 creator A5087343777 @default.
- W3089402258 date "2020-10-01" @default.
- W3089402258 modified "2023-10-14" @default.
- W3089402258 title "Data Security and Sensitive Data Protection using Privacy by Design Technique" @default.
- W3089402258 cites W2012025072 @default.
- W3089402258 doi "https://doi.org/10.1007/978-3-030-47560-4_14" @default.
- W3089402258 hasPublicationYear "2020" @default.
- W3089402258 type Work @default.
- W3089402258 sameAs 3089402258 @default.
- W3089402258 citedByCount "1" @default.
- W3089402258 countsByYear W30894022582021 @default.
- W3089402258 crossrefType "book-chapter" @default.
- W3089402258 hasAuthorship W3089402258A5028627559 @default.
- W3089402258 hasAuthorship W3089402258A5030817278 @default.
- W3089402258 hasAuthorship W3089402258A5087343777 @default.
- W3089402258 hasConcept C102938260 @default.
- W3089402258 hasConcept C10511746 @default.
- W3089402258 hasConcept C108827166 @default.
- W3089402258 hasConcept C111919701 @default.
- W3089402258 hasConcept C123201435 @default.
- W3089402258 hasConcept C144133560 @default.
- W3089402258 hasConcept C148730421 @default.
- W3089402258 hasConcept C165609540 @default.
- W3089402258 hasConcept C193934123 @default.
- W3089402258 hasConcept C2522767166 @default.
- W3089402258 hasConcept C2778656907 @default.
- W3089402258 hasConcept C38652104 @default.
- W3089402258 hasConcept C41008148 @default.
- W3089402258 hasConcept C69360830 @default.
- W3089402258 hasConcept C75684735 @default.
- W3089402258 hasConcept C79158427 @default.
- W3089402258 hasConceptScore W3089402258C102938260 @default.
- W3089402258 hasConceptScore W3089402258C10511746 @default.
- W3089402258 hasConceptScore W3089402258C108827166 @default.
- W3089402258 hasConceptScore W3089402258C111919701 @default.
- W3089402258 hasConceptScore W3089402258C123201435 @default.
- W3089402258 hasConceptScore W3089402258C144133560 @default.
- W3089402258 hasConceptScore W3089402258C148730421 @default.
- W3089402258 hasConceptScore W3089402258C165609540 @default.
- W3089402258 hasConceptScore W3089402258C193934123 @default.
- W3089402258 hasConceptScore W3089402258C2522767166 @default.
- W3089402258 hasConceptScore W3089402258C2778656907 @default.
- W3089402258 hasConceptScore W3089402258C38652104 @default.
- W3089402258 hasConceptScore W3089402258C41008148 @default.
- W3089402258 hasConceptScore W3089402258C69360830 @default.
- W3089402258 hasConceptScore W3089402258C75684735 @default.
- W3089402258 hasConceptScore W3089402258C79158427 @default.
- W3089402258 hasLocation W30894022581 @default.
- W3089402258 hasOpenAccess W3089402258 @default.
- W3089402258 hasPrimaryLocation W30894022581 @default.
- W3089402258 hasRelatedWork W10878359 @default.
- W3089402258 hasRelatedWork W1523377 @default.
- W3089402258 hasRelatedWork W1999344 @default.
- W3089402258 hasRelatedWork W269618 @default.
- W3089402258 hasRelatedWork W410025 @default.
- W3089402258 hasRelatedWork W4460643 @default.
- W3089402258 hasRelatedWork W6324969 @default.
- W3089402258 hasRelatedWork W7554620 @default.
- W3089402258 hasRelatedWork W789643 @default.
- W3089402258 hasRelatedWork W9594528 @default.
- W3089402258 isParatext "false" @default.
- W3089402258 isRetracted "false" @default.
- W3089402258 magId "3089402258" @default.
- W3089402258 workType "book-chapter" @default.