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

IBM Journey to AI blog

Foundation models can be trained to perform tasks such as data classification, the identification of objects within images (computer vision) and natural language processing (NLP) (understanding and generating text) with a high degree of accuracy. models are trained on IBM’s curated, enterprise-focused data lake.

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

Flipboard

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.

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

Alation

How much data processing that occurs will depend on the data’s state when ingested and how different the format is from the desired end state. Most data processing tasks are completed using ETL (Extract, Transform, Load) or ELT (Extract, Load Transform) processes.

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The Role of the Data Catalog in Data Security

Alation

Do we know the business outcomes tied to data risk management? These questions drive classification. Once you have data classification then you can talk about whether you need to tokenize and why, or anonymize and why, or encrypt and why, etc.” Guided Navigation Guided navigation helps data stewards locate sensitive data.

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Alation 2022.1: Customize Your Data Catalog

Alation

Airline Reporting Corporation (ARC) sells data products to travel agencies and airlines. Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed).

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AI that’s ready for business starts with data that’s ready for AI

IBM Journey to AI blog

Align your data strategy to a go-forward architecture, with considerations for existing technology investments, governance and autonomous management built in. Look to AI to help automate tasks such as data onboarding, data classification, organization and tagging.

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

Alation

How much data processing that occurs will depend on the data’s state when ingested and how different the format is from the desired end state. Most data processing tasks are completed using ETL (Extract, Transform, Load) or ELT (Extract, Load Transform) processes.