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How to Ensure Your New Cloud Data Lake Is Secure

Dataversity

Enterprises migrating on-prem data environments to the cloud in pursuit of more robust, flexible, and integrated analytics and AI/ML capabilities are fueling a surge in cloud data lake implementations. The post How to Ensure Your New Cloud Data Lake Is Secure appeared first on DATAVERSITY.

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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

The modern corporate world is more data-driven, and companies are always looking for new methods to make use of the vast data at their disposal. Cloud analytics is one example of a new technology that has changed the game. What is cloud analytics? How does cloud analytics work?

Analytics 203
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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning Blog

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. We then discuss how building on a secure foundation is essential for generative AI.

AWS 122
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Amazon SageMaker Feature Store now supports cross-account sharing, discovery, and access

AWS Machine Learning Blog

Features are used repeatedly by multiple teams, and feature quality is critical to ensure a highly accurate model. SageMaker Feature Store provides a secured and unified store to process, standardize, and use features at scale across the ML lifecycle. Features are inputs to ML models used during training and inference.

AWS 105
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10 Things AWS Can Do for Your SaaS Company

Smart Data Collective

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). In this article we will list 10 things AWS can do for your SaaS company. Data storage databases.

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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

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Choosing Your Snowflake Migration Approach: ‘Lift & Shift’ or Modernize?

phData

This blog was co-written by Ayush Kumar Singh and Mayank Singh When it comes to data management, one question that often arises is whether to lift and shift or modernize. In this context, ‘lift and shift’ refers to the process of moving data from one platform to another without making any changes to the data or how it is structured.