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Harmonize data using AWS Glue and AWS Lake Formation FindMatches ML to build a customer 360 view

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Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. This will open the ML transforms page.

AWS 92
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Data security: Why a proactive stance is best

IBM Journey to AI blog

Best practices for proactive data security Best cybersecurity practices mean ensuring your information security in many and varied ways and from many angles. Here are some data security measures that every organization should strongly consider implementing. Define sensitive data. Establish a cybersecurity policy.

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How foundation models and data stores unlock the business potential of generative AI

IBM Journey to AI blog

Together with data stores, foundation models make it possible to create and customize generative AI tools for organizations across industries that are looking to optimize customer care, marketing, HR (including talent acquisition) , and IT functions. models are trained on IBM’s curated, enterprise-focused data lake.

AI 58
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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

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Building Robust Data Pipelines: 9 Fundamentals and Best Practices to Follow

Alation

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.