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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Data transformation takes flight at Atlanta’s Hartsfield-Jackson airport

CIO Business Intelligence

At Atlanta’s Hartsfield-Jackson International Airport, an IT pilot has led to a wholesale data journey destined to transform operations at the world’s busiest airport, fueled by machine learning and generative AI. For instance, Delta “owns” or leases 169 gates out of the total 199 gates, making Atlanta the hub for that carrier.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially. This led to a complex and slow computations.

IoT 111
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Streamline AI-driven analytics with governance: Integrating Tableau with Amazon DataZone

AWS Big Data

Amazon DataZone is a data management service that makes it faster and easier for customers to catalog, discover, share, and govern data stored across AWS, on premises, and from third-party sources. You can now view your project’s subscribed data directly within Tableau and build dashboards.

Analytics 119
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Amazon OpenSearch Service launches flow builder to empower rapid AI search innovation

AWS Big Data

This middleware consists of custom code that runs data flows to stitch data transformations, search queries, and AI enrichments in varying combinations tailored to use cases, datasets, and requirements. The visual designer is recommended for helping you manage workflow projects. But what happens if we search for NBA?

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Organizations with legacy, on-premises, near-real-time analytics solutions typically rely on self-managed relational databases as their data store for analytics workloads. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

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What is data analytics? Analyzing and managing data for decisions

CIO Business Intelligence

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?