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Supercharge your data strategy: Integrate and innovate today leveraging data integration

IBM Journey to AI blog

The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it. Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models.

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How to accelerate your data monetization strategy with data products and AI

IBM Journey to AI blog

Data monetization strategy: Managing data as a product Every organization has the potential to monetize their data; for many organizations, it is an untapped resource for new capabilities. But few organizations have made the strategic shift to managing “data as a product.”

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How data stores and governance impact your AI initiatives

IBM Journey to AI blog

The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly. Here’s what’s involved in making that happen.

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Financial Data & AI: The Future of Business Intelligence

Defined.ai blog

It can quickly process large amounts of data, precisely identifying patterns and insights humans might overlook. Businesses can transform raw numbers into actionable insights by applying AI. For instance, an AI model can predict future sales based on past data, helping businesses plan better.

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How to choose the best AI platform

IBM Journey to AI blog

.” When observing its potential impact within industry, McKinsey Global Institute estimates that in just the manufacturing sector, emerging technologies that use AI will by 2025 add as much as USD 3.7 AI technology is quickly proving to be a critical component of business intelligence within organizations across industries.

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Achieve operational excellence with well-architected generative AI solutions using Amazon Bedrock

AWS Machine Learning Blog

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

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Five benefits of a data catalog

IBM Journey to AI blog

The solution also helps with data quality management by assigning data quality scores to assets and simplifies curation with AI-driven data quality rules.

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