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When is data too clean to be useful for enterprise AI?

CIO

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Data 211
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Taktile raises $20M to help fintech companies test and deploy decision-making models

TechCrunch

The two met while studying at Harvard and were both a part of the leadership team at QuantCo, a company building AI-powered apps for enterprise customers. While there, they found that many automated decisions were poorly designed, hardly ever tested properly and required a lot of engineering capacity — ultimately leading to guesswork.

Fintech 228
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Accenture forges own path to improve attack surface management

CIO

We’ve always had a strong security posture, but as we’ve been growing, we noticed that we had weaknesses in our defenses,” says Kristian Burkhardt, Accenture CISO. Burkhardt and his team first noticed gaps in their security posture when doing crowdsourced penetration testing.

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How to build a successful agile development culture – and why your business needs one

CIO

To keep pace with the growing complexity of software development, organizations have spent years working to implement agile practices into their developer experience. It enables teams to deliver value faster, with greater quality and predictability, and greater aptitude to respond to change.

Agile 148
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How real-time operational insights drive superior tech platform development

CIO

As SaaS solutions gain greater market share, and build mindshare, operational know-how is becoming critical to both their development and evolution. One of the biggest issues for any development team is obtaining real and timely user feedback. Traditional development approaches can also cause lengthy release cycles.

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3 questions to ask before adopting 5G for IoT

CIO

The power of 5G networks will one day usher in new generations of IoT applications, but large-scale adoption may still be a long way off. They design, develop, and manufacturer products and solutions to power the new cell towers, a critical environment where speed and uptime define the service. “If

IoT 189
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Interpreting predictive models with Skater: Unboxing model opacity

O'Reilly Media - Data

Data Scientist Cathy O’Neil has recently written an entire book filled with examples of poor interpretability as a dire warning of the potential social carnage from misunderstood models—e.g., There is also a trade off in balancing a model’s interpretability and its performance.