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How to build a successful AI strategy

IBM Big Data Hub

An AI strategy allows organizations to purposefully harness AI capabilities and align AI initiatives with overall business objectives. It will also determine the talent the organization needs to develop, attract or retain with relevant skills in data science, machine learning (ML) and AI development.

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Cloud Analytics Powered by FinOps

Cloudera

Agility, innovation, and time-to-value are the key differentiators cloud service providers (CSP) claim to help organizations speed up digital transformation projects and business objectives. However, the reality is that the “move to cloud” is a turbulent flight for many of them. Why FinOps?

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4 Recommendations for Maximizing ROI in Artificial Intelligence Solutions

CDW Research Hub

As AI use cases start meeting their initial business objectives, initial infrastructure decisions can either accelerate the deployment of subsequent use cases or stall them. Businesses should be ready to adapt to these outcomes while being flexible regarding infrastructure. Understanding the workflow requirements is critical.

ROI 79
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Automating Model Risk Compliance: Model Validation

DataRobot Blog

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. If we have already built out a model for a business application, how do we ensure that it is working to our expectations? Conceptual Soundness of the Model.

Risk 52
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How Encored Technologies built serverless event-driven data pipelines with AWS

AWS Big Data

Encored develops machine learning (ML) applications predicting and optimizing various energy-related processes, and their key initiative is to predict the amount of power generated at renewable energy power plants. For instructions on creating an ECR repository, refer to Creating a private repository. northeast-2.amazonaws.com

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What is digital transformation? A necessary disruption

CIO Business Intelligence

S&P Global Market Intelligence has found that digitally driven organizations outperform digitally delayed ones across a host of key metrics, including customer satisfaction, average time to respond to customer inquiries, customer lifetime value, customer acquisition, and marketing ROI.

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Ontotext Invents the Universe So You Don’t Need To

Ontotext

The goal is to make it easier to encode the business knowledge of personnel such as business analysts who have the best understanding of the business and the most well-rounded domain knowledge. Semantic Objects and the Semantic Objects Modeling Language (SOML) is a simple way to describe business objects or domain objects.