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The success of GenAI models lies in your data management strategy

CIO Business Intelligence

However, this enthusiasm may be tempered by a host of challenges and risks stemming from scaling GenAI. As the technology subsists on data, customer trust and their confidential information are at stake—and enterprises cannot afford to overlook its pitfalls.

Strategy 143
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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. Data Platforms. Data Integration and Data Pipelines. Data preparation, data governance, and data lineage.

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The DataOps Vendor Landscape, 2021

DataKitchen

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines.

Testing 300
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How to Carry Out an Effective Data Migration: Strategies and Best Practices

Smart Data Collective

There can be many reasons for you to migrate data, such as overhauling the entire system, upgrading the current database, merge the data with the new source, or expanding the existing one. Make sure that you adhere to the best possible migration strategy, regardless of why it is a must for successful data migration.

Strategy 108
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Achieve data resilience using Amazon OpenSearch Service disaster recovery with snapshot and restore

AWS Big Data

Disaster recovery is vital for organizations, offering a proactive strategy to mitigate the impact of unforeseen events like system failures, natural disasters, or cyberattacks. In Disaster Recovery (DR) Architecture on AWS, Part I: Strategies for Recovery in the Cloud , we introduced four major strategies for disaster recovery (DR) on AWS.

Snapshot 103
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How to accelerate your data monetization strategy with data products and AI

IBM Big Data Hub

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. Doing so can increase the quality of data integrated into data products.

Strategy 103
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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive. Developers, data architects and data engineers can initiate change at the grassroots level from integrating sustainability metrics into data models to ensuring ESG data integrity and fostering collaboration with sustainability teams.

IT 59