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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries.

Big Data 275
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A summary of Gartner’s recent DataOps-driven data engineering best practices article

DataKitchen

On 24 January 2023, Gartner released the article “ 5 Ways to Enhance Your Data Engineering Practices.” How do you scale an organization without hiring an army of hard-to-find data engineering talent? are more efficient in prioritizing data delivery demands.” Summary: 10x your data engineering game.

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The Failed Promises of Digital Transformation and What to Do About It

Ontotext

These failures are at least partly due to the absence of graph technologies, at the center of those transformations, allowing companies to “connect the dots” across their data to drive optimal outcomes. If context and relationships between things are important, then graph technologies should be at the center of the solution.

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How Can Manufacturing Data Help Your Organization?

Sisense

In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. The world of data in modern manufacturing. Manufacturing companies that adopted computerization years ago are already taking the next step as they transform into smart data-driven organizations.

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How to choose the best AI platform

IBM Big Data Hub

.” When observing its potential impact within industry, McKinsey Global Institute estimates that in just the manufacturing sector, emerging technologies that use AI will by 2025 add as much as USD 3.7 This unified experience optimizes the process of developing and deploying ML models by streamlining workflows for increased efficiency.

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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Risk Management (most likely within context of governance).