Remove Forecasting Remove Metrics Remove Risk Management
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5 tips for better business value from gen AI

CIO Business Intelligence

Specify metrics that align with key business objectives Every department has operating metrics that are key to increasing revenue, improving customer satisfaction, and delivering other strategic objectives. Below are five examples of where to start. Gen AI holds the potential to facilitate that.

Sales 143
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Where CIOs should place their 2025 AI bets

CIO Business Intelligence

times compared to 2023 but forecasts lower increases over the next two to five years. 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.

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10 Technical Blogs for Data Scientists to Advance AI/ML Skills

DataRobot Blog

Taking a Multi-Tiered Approach to Model Risk Management. Understand why organizations need a three-pronged approach to mitigating risk among multiple dimensions of the AI lifecycle and what model risk management means to today’s AI-driven companies. Forecast Time Series at Scale with Google BigQuery and DataRobot.

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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams. However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive.

IT 59
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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. It ensures that all relevant data and information is consolidated, evaluated and presented in a clear and concise form.

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How to Manage Risk with Modern Data Architectures

Cloudera

Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs. Financial institutions can use ML and AI to: Support liquidity monitoring and forecasting in real time.

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5 signs your agile practices will lead to digital disaster

CIO Business Intelligence

Agile is an amazing risk management tool for managing uncertainty, but that’s not always obvious.” The key is recognizing that planning must be an agile discipline, not a standalone activity performed independently of agile teams. He recommends that leaders identify a metric that focuses on value to the customer.