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The journey to a mature asset management system

IBM Big Data Hub

Asset management and technological innovation Advancements in technology underpin the need for holistic grid asset management, making the assets in the grid smarter and equipping the workforce with smart tools. Robots and drones perform inspections by using AI-based visual recognition techniques.

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Best BI Tools Examples for 2024: Business Intelligence Software

FineReport

In addition to these advancements, another prominent trend in data analysis is the growing impact of data visualization. This trend addresses the need for users to interpret complex datasets through interactive visuals that facilitate a deeper understanding of the underlying information.

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Cropin’s agriculture industry cloud to provide apps, data frameworks

CIO Business Intelligence

Cropin Apps, as the name suggests, comprises applications that support global farming operations management, food safety measures, supply chain and “farm to fork” visibility, predictability and risk management, farmer enablement and engagement, advance seed R&D, production management, and multigenerational seed traceability.

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A Guide To Starting A Career In Business Intelligence & The BI Skills You Need

datapine

To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools. For example, you could be the one to extract actionable insights from specific retail KPIs that need to be visualized and presented during a meeting. BI developer. BI engineer.

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Why you should care about debugging machine learning models

O'Reilly on Data

In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. While our analysis of each method may appear technical, we believe that understanding the tools available, and how to use them, is critical for all risk management teams.

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Automating Model Risk Compliance: Model Monitoring

DataRobot Blog

A prerequisite in measuring a deployed model’s evolving performance is to collect both its input data and business outcomes in a deployed setting. With this data in hand, we are able to measure both the data drift and model performance, both of which are essential metrics in measuring the health of the deployed model.

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How PwC and SAP are doing right by helping clients unlock ESG value

CIO Business Intelligence

From 1 January 2024, the provisions relating to supplier risk management will also apply to companies with more than 1,000 employees. CYVC offers the possibility to process large amounts of data (semi-) automatically in a short time frame and identifies risks based on different assessment methods.