TruFactor

3 imperatives for CDOs to prepare for the "Next Normal": buff.ly/2xjAsc1

80% of Americans are concerned about their personal data. @CDPInstitute highlights the opportunity to adopt Responsible Data Use standards. buff.ly/330t15p #dataprivacy #regulations #trust

Time to act and choose between a reactive compliance-oriented position or building proper governance to foster trust with your board of directors, your customers, and regulators. buff.ly/2QI6bd0

CDP Institute highlights Responsible Data Use standards: teapaw.org/CDPInstitute/status/13…

Current data practices emphasize "hoarding and value extraction" resulting in distrust. We need new institutions, structures & stewards to unlock value: buff.ly/2W1JlQU

Trust, Transparency, and Type of Data. Not all data is created equal - these "3Ts" determine consumers expectations. buff.ly/36yFc9h

Data privacy needs to be more than a compliance or regulatory effort. Genuine commitment is needed to rebuild consumer trust. buff.ly/3fnvzi4

50%+ of consumers don't trust companies to collect or use personal data ethically, and 90% say that they need to establish data responsibility principles: buff.ly/34ltjpN

More insights on the differences between AI and software development and best practices from leaders in Data and AI: buff.ly/3iDRG5B

Thanks to everyone at @InMobi InMobi - and especially our TruFactor team - for all that you do! teapaw.org/InMobi/status/12940762…

KPMG reports that 91% of consumers say corporations need data responsibility principles. How? TruFactor outlines fundamentals of Responsible Data Use: buff.ly/2Fb7ApT

Is building expertise in Machine Learning Ops the next priority for addressing data concerns and scaling AI? Read more from VentureBeat: buff.ly/33G2qfM

Democratizing AI demands Data Governance to ensure visibility into data’s origins and modifications, understanding purpose of data collection, and proper safeguards. buff.ly/3d8dzae

Not using data isn't the answer. Adopting Standards for Responsibly Sourced Data is: buff.ly/2Nq2Tt3

Another view on the data science dream team from @HarvardBiz - define talents, not team roles: buff.ly/2GlkxLR

McKinsey finds that 30% of enterprise time is spent on non-value-added tasks because of poor data quality and availability: buff.ly/3eHGB20

Catch-up on the latest privacy research from FTC's PrivacyCon2020: buff.ly/2CCuvcV

See how "PoFMU" powers our processing pipelines and data structures to support answering diverse use cases across industries: buff.ly/2xiUpQh

Data is the bedrock of AI. Hear more about identifying the right datasets and optimizing processing pipelines from VB Transform: buff.ly/2OoVdb8

Innovation and Privacy go hand in hand. Regaining consumer trust by adopting Responsible Data Use standard is critical to harnessing AI: buff.ly/2Nq2Tt3