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Linking ESG Programs to Corporate Financial Performance: An Econometric Analysis Approach

CSM Magazine

Understanding the ESG Framework and Its Role in Corporate Finance In the evolving landscape of corporate finance, ESG principles are gaining prominence. Furthermore, the integration of digital technologies, including artificial intelligence, blockchain, and big data, augments these ESG capabilities.

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10 Unique Use Cases for Speech Analytics

Expivia

You would react to certain complaints or compliments, bring it to marketing, or finance, or product, and still, they might shoo you away. Generating Marketing Data. No longer are we looking at serving the customer with our call center, we are collecting that big data and sourcing it. Proactive Customer Service.

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Amazon SageMaker built-in LightGBM now offers distributed training using Dask

AWS Machine Learning

The supported data format can be either CSV or Parquet. Extensive benchmarking experiments on three publicly available datasets with various settings are conducted to validate its performance. Distributed training is a technique that allows for the parallel processing of large amounts of data across multiple machines or devices.

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A review of purpose-built accelerators for financial services

AWS Machine Learning

SIMD describes computers with multiple processing elements that perform the same operation on multiple data points simultaneously. SIMT describes processors that are able to operate on data vectors and arrays (as opposed to just scalars), and therefore handle big data workloads efficiently.

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What Is Digital Transformation? A Complete Guide

Cincom

Companies use advanced technologies like AI, machine learning, and big data to anticipate customer needs, optimize operations, and deliver customized experiences. Creating robust data governance frameworks and employing tools like machine learning, businesses tend derive actionable insights to achieve a competitive edge.

CRM 40
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Call Center Analytics: How to Analyze Call Center Data

Balto

But modern analytics goes beyond basic metricsit leverages technologies like call center data science, machine learning models, and big data to provide deeper insights. Predictive Analytics: Uses historical data to forecast future events like call volumes or customer churn. What is contact center big data analytics?

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MLOps foundation roadmap for enterprises with Amazon SageMaker

AWS Machine Learning

Data scientists collaborate with ML engineers in a separate environment to build robust and production-ready algorithms and source code, orchestrated using Amazon SageMaker Pipelines. The generated models are stored and benchmarked in the Amazon SageMaker model registry.