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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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Sure, Trust Your Data… Until It Breaks Everything: How Automated Data Lineage Saves the Day

Octopai

In today’s data-centric world, organizations often tout data as their most valuable asset. However, many struggle to maintain reliable, trustworthy data amidst complex, evolving environments. This challenge is especially critical for executives responsible for data strategy and operations.

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Improve power utility operational efficiency using smart sensor data and Amazon QuickSight

AWS Big Data

Different communication infrastructure types such as mesh network and cellular can be used to send load information on a pre-defined schedule or event data in real time to the backend servers residing in the utility UDN (Utility Data Network).

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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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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

The CLEA dashboards were built on the foundation of the Well-Architected Lab. For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. Overview of the BMW Cloud Data Hub At the BMW Group, Cloud Data Hub (CDH) is the central platform for managing company-wide data and data solutions.

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DataOps Observability: Taming the Chaos (Part 2)

DataKitchen

Part 2: Introducing Data Journeys. Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately.

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Alation & Bigeye: A Potent Partnership for Data Quality

Alation

Alation and Bigeye have partnered to bring data observability and data quality monitoring into the data catalog. Read to learn how our newly combined capabilities put more trustworthy, quality data into the hands of those who are best equipped to leverage it. trillion each year due to poor data quality.