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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

CIOs feeling the pressure will likely seek more pragmatic AI applications, platform simplifications, and risk management practices that have short-term benefits while becoming force multipliers to longer-term financial returns. Even this breakdown leaves out data management, engineering, and security functions.

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Why you should care about debugging machine learning models

O'Reilly on Data

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. That’s where model debugging comes in. Sensitivity analysis.

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From project to product: Architecting the future of enterprise technology

CIO Business Intelligence

By articulating fitness functions automated tests tied to specific quality attributes like reliability, security or performance teams can visualize and measure system qualities that align with business goals. Technical foundation Conversation starter : Are we maintaining reliable roads and utilities, or are we risking gridlock?

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How BI Improves Risk Management within Organisations

Sisense

As businesses adapt to the pandemic and shift to new norms, risk mitigation strategies have become as normal and ubiquitous as having a fire escape in the office. Smarter, AI-driven learning and development initiatives will help mitigate risk in our rapidly evolving world. Minimising risk by ‘infusing’ AI. ” Anna adds.

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A Detailed Introduction on Data Lakes and Delta Lakes

Analytics Vidhya

You may run different types of analytics, from dashboards and visualizations to big data processing, real-time analytics, and machine […]. Introduction A data lake is a central data repository that allows us to store all of our structured and unstructured data on a large scale.

Data Lake 271
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How Big Data Impacts The Finance And Banking Industries

Smart Data Collective

Nowadays, terms like ‘Data Analytics,’ ‘Data Visualization,’ and ‘Big Data’ have become quite popular. Here are a few of the advantages of Big Data in the banking and financial industry: Improvement in risk management operations. Big Data provides financial and banking organizations with better risk coverage.

Big Data 145
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Why HR professionals struggle with big data

CIO Business Intelligence

Solid reporting provides transparent, consistent and combined HR metrics essential for strategic planning, risk management and the management of HR measures. A central measure here is the definition and visualization of control and monitoring key figures.