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Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources.

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Understanding Structured and Unstructured Data

Sisense

Different types of information are more suited to being stored in a structured or unstructured format. Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both.

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Build a decentralized semantic search engine on heterogeneous data stores using autonomous agents

AWS Big Data

Large language models (LLMs) such as Anthropic Claude and Amazon Titan have the potential to drive automation across various business processes by processing both structured and unstructured data. Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

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Get maximum value out of your cloud data warehouse with Amazon Redshift

AWS Big Data

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.

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How a Discovery Data Warehouse, the next evolution of augmented analytics, accelerates treatments and delivers medicines safely to patients in need

Cloudera

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

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Cloudera Named a Visionary in the Gartner MQ for Cloud DBMS

Cloudera

This recognition is a testament to our vision and ability as a strategic partner to deliver an open and interoperable Cloud data platform, with the flexibility to use the best fit data services and low code, no code Generative AI infused practitioner tools.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.