Remove Forecasting Remove Optimization Remove Risk Management
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Modular architecture drives productivity and risk management at Gilbane

CIO Business Intelligence

The product — a building or bridge — might be physical but it can be represented digitally, through virtual design and construction, she says, with elements of automation that can optimize and streamline entire business processes for how physical products are delivered to clients. So they’ll be patient when it comes to ROI.

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Building Tax Planning into Enterprise Risk Management Strategies

Jet Global

It follows that tax teams should think about how they can make significant contributions to the ERM planning process by providing short, mid- and long-term ETR forecasts based on accurate financial information. Reputational management is another driver for boards to build tax planning into ERM strategies.

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Should I Stay or Go? Migrating to AI-Enabled Applications

David Menninger's Analyst Perspectives

The research finds the greatest inclination to spend is in sales performance management, which I interpret to mean that the participants see this area as having the highest potential to generate profit through gains in sales productivity and, therefore, increase revenue.

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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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AI and generative AI are revolutionizing manufacturing…here’s how

CIO Business Intelligence

The timing for these advancements is optimal as the industry grapples with skilled labor shortages, supply chain challenges, and a highly competitive global marketplace. Process optimization In manufacturing, process optimization that maximizes quality, efficiency, and cost-savings is an ever-present goal.

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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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Cloud Technology Powers Research on PSA Software

Smart Data Collective

The study indicates that over one-third of non-PSA users are poised to transition to a PSA system within the next three years, aligning with forecasts that the PSA market will double during this period. One of the benefits is by making DevOps easier to optimize. Why Do Businesses Seek to Use PSA Systems?

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