Our team designed and developed solutions that suit the needs of enterprise big data management and analytics market.
My role:
Strategy, Planning, Prototyping, UI/UX Guidelines
Duration:
4 months
Outcome:
SaaS, NPS +14 points
In order to adapt to rising concerns regarding in-house data compliance to PII (personally identifiable information), PCI DSS (payment card industry data security standard), and/or GDPR (general data protection regulation).
We determined that the businesses are also in need of security, protection, and management with their data sources (files, databases, etc.) to migrate data from legacy to cloud (for system and impact analysis).
How might we help businesses secure their data so that they can accelerate migration to cloud?
Features workshop
After the stakeholder workshop, we aimed at solving the problem by successfully helping businesses discover, classify, and manage data sources at risk of data compliance; and by helping businesses understand areas of improvement in managing both unstructured and structured forms of data using named entity recognition in text analytics.
dEFINING problem space
Defining private information as information about a living individual, which can identify an individual through personal characteristics and or attributes such as name and resident number, I arrived at defining the levels of risk exposure by type of personal information.
Wireframing
design specs
rapid Prototyping
Along with the feature specs and the design guides, the prototype is handed off to the developers to better communicate the intents behind each interaction.
product demo
Throughout the phases of the development cycle, I actively communicated with front-end developer in our team to make sure the development constraints aren't impeding the overall experience of the platform.
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