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How Will The Cloud Impact Data Warehousing Technologies?

Smart Data Collective

Data warehouse, also known as a decision support database, refers to a central repository, which holds information derived from one or more data sources, such as transactional systems and relational databases. The data collected in the system may in the form of unstructured, semi-structured, or structured data.

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Building and Evaluating GenAI Knowledge Management Systems using Ollama, Trulens and Cloudera

Cloudera

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes. This contextualization is possible thanks to RAG.

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Large Language Models and Data Management

Ontotext

I did some research because I wanted to create a basic framework on the intersection between large language models (LLM) and data management. But there are also a host of other issues (and cautions) to take into consideration. The technology is very new and not well understood. taxonomies, ontologies , internal data structures).

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Do Large Language Models Dream of Knowledge Graphs – Impressions from Day 2 At SEMANTiCS 2023

Ontotext

I learned that fact from a comment in the audience on the second day of SEMANTICS 2023 – the European conference series focused on semantic technologies ever since 2005. Source: SWC Aidan concluded by saying that LLMs can make knowledge graphs more usable and widespread as a technology. I didn’t either.

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Migrate a petabyte-scale data warehouse from Actian Vectorwise to Amazon Redshift

AWS Big Data

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The system had an integration with legacy backend services that were all hosted on premises. Vishal Balani is a Sr.

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Reflections on the Knowledge Graph Conference 2023

Ontotext

The event attracts individuals interested in graph technology, machine learning and natural language processes in numerous verticals, including publishing, government, financial services, manufacturing and retail. This message resonates with the market positioning of Ontotext as a trusted, stable option for demanding data-centric use cases.

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5 Pain Points of Moving Data to the Cloud and Strategies for Success

Alation

We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. Accompanying this acceleration is the increasing complexity of data. Complex data management is on the rise.