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

datapine

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

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The Foundations of a Modern Data-Driven Organisation: Change from Within (part 2 of 2)

Cloudera

In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. Collecting workforce data as a tool for talent management. Data enables Innovation & Agility.

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5 Ways Data Engineers Can Support Data Governance

Alation

However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public.

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The Benefits of Data Governance in Banks and Financial Institutions

Alation

Banks collect and manage a lot of sensitive data. And, the data collection doesn’t stop there — rich insights like transactions and purchasing information help to round out customer profiles. Enabling data access is just the first step. This data also needs to meet quality standards to be trusted.

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12 considerations when choosing MES software

IBM Big Data Hub

If you are experiencing inefficiencies, bottlenecks, quality control challenges or compliance issues in your production processes, an MES can provide real-time data and performance analysis across production lines to identify and address these issues promptly. But for a large organization, it’s just one of many sources.

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Smart manufacturing technology is transforming mass production

IBM Big Data Hub

artificial intelligence (AI) applications, the Internet of Things (IoT), robotics and augmented reality, among others) to optimize enterprise resource planning (ERP), making companies more agile and adaptable. Ensure that sensitive data remains within their own network, improving security and compliance.

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The Power of Ontologies and Knowledge Graphs: Practical Examples from the Financial Industry

Ontotext

Case Study In their talk: How Knowledge Graphs and Graph Databases Take Your Data Further, presented at Ontotext’s Knowledge Graph Forum 2022, Ragini Okhandiar and Krishna Potluri from JPMorgan Chase & Co. It is reused in modeling the publication of entity data or regulatory-mandated data exchange, as seen in the example provided below.