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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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Simplify Metrics on Apache Druid With Rill Data and Cloudera

Cloudera

Co-author: Mike Godwin, Head of Marketing, Rill Data. Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. Deploying metrics shouldn’t be so hard. Cloudera Data Warehouse).

Metrics 86
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Navigating the Chaos of Unruly Data: Solutions for Data Teams

DataKitchen

Identifying Anomalies: Use advanced algorithms to detect anomalies in data patterns. Establish baseline metrics for normal database operations, enabling the system to flag deviations as potential issues. It is essential to educate all users on the importance of data integrity and their role in maintaining it.

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Mastering Data Analysis Report and Dashboard

FineReport

As we explore examples of data analysis reports and interactive report data analysis dashboards, we embark on a journey to unravel the nuanced art of transforming raw data into meaningful narratives that empower decision-makers. Try FineReport Now 1. Try FineReport Now 1.1 Try FineReport Now 1.1

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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

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Cloudera DataFlow Designer: The Key to Agile Data Pipeline Development

Cloudera

Once a draft has been created or opened, developers use the visual Designer to build their data flow logic and validate it using interactive test sessions. In the DataFlow Designer, you can create Test Sessions to turn the canvas into an interactive interface that gives you all the feedback you need to quickly iterate your flow design.

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

AWS Big Data

In this series of posts, we walk you through how we use Amazon QuickSight , a serverless, fully managed, business intelligence (BI) service that enables data-driven decision making at scale. The AWS Glue Data Catalog contains the table definitions for the smart sensor data sources stored in the S3 buckets.