Ontotext

JULY 24, 2023

A Few Cautions LLM references a huge amount of data to become truly functional, making it a quite expensive and time consuming effort to train the model. Supercomputers (and other components of infrastructure) along with new approaches to data architecture (with billions of parameters) are needed.

Modeling 98

Modeling Management Structured Data Data Architecture 98

CIO Business Intelligence

JUNE 28, 2023

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs. This allowed us to derive insights more easily.”

Digital Transformation 99

Digital Transformation Cost-Benefit Informatics Data mining 99

AWS Big Data

JANUARY 24, 2023

This post explains how to create a design that automatically backs up Amazon Simple Storage Service (Amazon S3), the AWS Glue Data Catalog, and Lake Formation permissions in different Regions and provides backup and restore options for disaster recovery. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

Data Architecture 68

Data Architecture Metadata Data Lake Snapshot 68

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. The following diagram illustrates the solution architecture. This post is co-written with Eliad Gat and Oded Lifshiz from Orca Security. Orca addressed this in several ways.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

IBM Big Data Hub

JANUARY 17, 2023

You can select a hybrid integration strategy that aligns with your organization’s business strategy to meet the needs of your data consumers wanting to access and utilize the data. Data science and MLOps. AI is no longer experimental. Start a trial. Start a trial. AI governance.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

O'Reilly on Data

SEPTEMBER 11, 2019

Each has different “expectations” about the motion of the data it consumes. In the second place, data-in-motion behaves less predictably than data-at rest. It’s more difficult to monitor, control, and optimize data flows in a data-in-motion paradigm. New trends in data architecture and data services.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20