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Automate alerting and reporting for AWS Glue job resource usage

AWS Big Data

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

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

AWS Big Data

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform.

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Simplify Metrics on Apache Druid With Rill Data and Cloudera

Cloudera

As creators and experts in Apache Druid, Rill understands the data store’s importance as the engine for real-time, highly interactive analytics. Cloudera Data Warehouse and Rill Data—built on Apache Hive and Druid, respectively—can be connected using the Hive-Druid Integration. Cloudera Data Warehouse).

Metrics 83
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Happy Birthday, CDP Public Cloud

Cloudera

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. That Was Then. This is Now. New Services.

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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

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. But first, let’s define what data quality actually is. Data profiling is an essential process in the DQM lifecycle.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 77
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What is a DataOps Engineer?

DataKitchen

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines.

Testing 152