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What is Data Lakehouse Architecture?

Data lakehouse architecture allows organizations to manage both structured and unstructured data within a single, scalable system. It supports diverse use cases like business reporting, real-time analytics, and machine learning, all within a single system. This flexibility is made possible through five foundational layers that work together to collect, store, manage, and deliver data efficiently.

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What Is a Data Lakehouse? Benefits, Features & Platforms

A data lakehouse is a system that brings together the best features of both data lakes and data warehouses. It allows businesses to store all kinds of data, structured like tables or unstructured like images or logs, in one place.
In the past, companies used data lakes to store raw data and data warehouses for organized, ready-to-use data. But this often caused problems like data duplication and slow workflows.

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What Is Enterprise AI?

Enterprise AI refers to the integration of artificial intelligence capabilities into core business functions, systems, and workflows across an organization. Unlike generic AI, which may focus on individual tasks or consumer applications, Enterprise AI is built for scale, security, governance, and business alignment.

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Top 10 Generative AI Use Cases Across Industries

Generative AI use cases in marketing include automated content creation, campaign optimization, and audience targeting. Models trained on behavioral and transactional data generate ad copy, product descriptions, emails, and social media content tailored to segmented audiences.

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What is a Data Governance Framework?
A data governance framework is a structured approach that defines how an organization manages its data assets. It outlines the policies, roles, responsibilities, processes, and standards needed to ensure data is accurate, consistent, secure, and used responsibly across the organization.