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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

As the retail industry witnesses a shift towards a more digital, on-demand consumer base, AI is becoming the secret weapon for retailers to better understand and cater to this evolving consumer behavior. Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content.

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IBM and TechD partner to securely share data and power insights with gen AI

IBM Big Data Hub

Also, Db2 seamlessly integrates with watsonx Assistant’s natural language processing capabilities to analyze unstructured data and derive insights. NeuralSeek prioritizes client security and privacy by encrypting data both in transit and at rest, safeguarding it from unauthorized access and preserving its confidentiality.

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

In today’s digital age where data stands as a prized asset, generative AI serves as the transformative tool to mine its potential. Adopting AI in business at scale is not without its challenges, including data privacy concerns, integration complexities and the need for skilled personnel.

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The most valuable AI use cases for business

IBM Big Data Hub

Promote cross- and up-selling Recommendation engines use consumer behavior data and AI algorithms to help discover data trends to be used in the development of more effective up-selling and cross-selling strategies, resulting in more useful add-on recommendations for customers during checkout for online retailers.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Big Data Hub

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements.

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Master? ?Data? ?Management? ?Trends? ?to? ?Get? ?Ahead? ?With?

Reltio

Second-generation MDMs: Incorporate truly multidomain and omnichannel strategies for real-time insights that use machine learning and AI for data governance. . As Forrester puts it in a 2019 report on master data management, second-generation MDMs prioritize agility over compliance. 2 Hyper-Personalization. Examples: .

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