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industrial data

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DataFunTalk
DataFunTalk
Jul 20, 2023 · Databases

Industrial Digital Transformation and Intelligent Connected Vehicles: Best Practices with YMatrix Hyper‑Converged Database

The article presents a practitioner’s view on industrial digital transformation, using intelligent connected vehicles as a case study to illustrate trends, value, challenges, and a comprehensive solution that combines data‑centric architecture, unified standards, a high‑performance YMatrix hyper‑converged database, and AI‑driven predictive maintenance.

Cloud ComputingYMatrixbig-data
0 likes · 18 min read
Industrial Digital Transformation and Intelligent Connected Vehicles: Best Practices with YMatrix Hyper‑Converged Database
DataFunSummit
DataFunSummit
Mar 25, 2023 · Operations

Industrial Data and Intelligent Algorithms for Production Scheduling Optimization

This article explores how industrial data and intelligent algorithms can drive production scheduling optimization, discussing strategic significance, challenges, data‑driven algorithmic approaches, key scientific problems, and future trends in smart manufacturing, with insights from academic research and industry applications.

AI algorithmsOptimizationindustrial data
0 likes · 13 min read
Industrial Data and Intelligent Algorithms for Production Scheduling Optimization
DataFunSummit
DataFunSummit
Nov 15, 2022 · Big Data

Industrial Data Governance: Challenges, Practices, and Insights

Industrial data governance, essential for digital transformation, faces challenges such as data heterogeneity, volume, quality, and integration across the value chain, and the presentation outlines background, practical approaches, strategic thinking, and a phased, demand‑driven model to enhance data quality, assetization, and business value.

Data AssetizationData Governancebig-data
0 likes · 24 min read
Industrial Data Governance: Challenges, Practices, and Insights
DataFunSummit
DataFunSummit
Mar 2, 2022 · Databases

Industrial Data Analysis: Choosing Between Normalized and Dimensional Data Warehouse Modeling

The article examines industrial data analysis and compares normalized (entity‑relationship) modeling with dimensional (star/snowflake) modeling for data warehouses, highlighting their strengths, weaknesses, and selection criteria based on an enterprise's data‑intelligence maturity and project goals.

Data GovernanceData Warehousebig-data
0 likes · 16 min read
Industrial Data Analysis: Choosing Between Normalized and Dimensional Data Warehouse Modeling