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

Cloudera

The report classified employees’ reasons for leaving into six broad categories such as growth opportunity and job security, demonstrating the importance of using performance data, data collected from voluntary departures and historical data to reduce attrition for strong performers and enhance employees’ well-being.

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

datapine

To work effectively, big data requires a large amount of high-quality information sources. Where is all of that data going to come from? After examining their data, UPS found that trucks turning left were costing them a lot of money. Big data enables automated systems by intelligently routing many data sets and data streams.

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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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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.

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CIOs rise to the ESG reporting challenge

CIO Business Intelligence

CIOs — who sign nearly half of all net-zero services deals with top providers, according to Everest Group analyst Meenakshi Narayanan — are uniquely positioned to spearhead data-enabled transformation for ESG reporting given their data-driven track records. Most companies find themselves in a similar situation.

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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. What’s the biggest challenge manufacturers face right now?