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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.

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Augmented Analytics Must Provide Data Quality and Insight!

Smarten

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics? There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data.

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AWS Glue Data Quality is Generally Available

AWS Big Data

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

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Your Generative AI LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers

DataKitchen

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. DataOps ensures that the data retrieved is relevant, high-quality, and up-to-date.

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Optimizing Risk and Exposure Management – Roundtable Highlights

Cloudera

Manage the extreme risk data points – As part of the analysis of the model output, it is critical to assess whether the shocks are realistic or true outliers. . Contagion Impacts – interactions of different risks and related impacts were brought into focus by the pandemic and it highlighted the area that need attention.

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Modernizing and optimizing enterprise reporting [Infographic]

BI-Survey

Modernizing and optimizing enterprise reporting – or classical BI – has not been such a priority for many of today’s organizations, even though it constitutes the backbone of information supply for decision support. Data management has always been a challenge for companies. Modernize data management to guarantee high data quality.

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

This introduces the need for both polling and pushing the data to access and analyze in near-real time. From an operational standpoint, we designed a new shared responsibility model for data ingestion using AWS Glue instead of internal services (REST APIs) designed on Amazon EC2 to extract the data.