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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. Cleaning, refining, and aligning your data to shared meaning is the right strategic approach.

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

Ontotext

LLMs] call into question a fundamental tenet of Data Management: that in order to address non-trivial information needs, the first step is to explicitly structure data in order to lift them from the ambiguous swamp of our human language. Thankfully, lt-innovate.org already did a concise wrap-up.

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Data, data everywhere: why you need an enterprise data platform

CIO Business Intelligence

Be prepared to do some refactoring in respect to networking, storage, and a host of other resources. Its highly scalable, real-time streaming analytics engine that ingests, curates, and analyses data for key insights and immediate actionable intelligence. Be prepared to backtrack.

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Reflections on the Knowledge Graph Conference 2023

Ontotext

This message resonates with the market positioning of Ontotext as a trusted, stable option for demanding data-centric use cases. During the conference, the organizers hosted a separate track called the Healthcare and Life Sciences Symposium. Knowledge graphs will continue to be essential for AI in the era of ChatGPT and LLM.

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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.

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Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

AWS Big Data

Spark SQL is an Apache Spark module for structured data processing. host') export PASSWORD=$(aws secretsmanager get-secret-value --secret-id $secret_name --query SecretString --output text | jq -r '.password') or later installed. OutputKey=='HiveSecretName'].OutputValue" OutputKey=='HiveSecretName'].OutputValue"

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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.