Remove Data Analytics Remove Data Quality Remove Data Warehouse
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The next generation of Amazon SageMaker: The center for all your data, analytics, and AI

AWS Big Data

This week on the keynote stages at AWS re:Invent 2024, you heard from Matt Garman, CEO, AWS, and Swami Sivasubramanian, VP of AI and Data, AWS, speak about the next generation of Amazon SageMaker , the center for all of your data, analytics, and AI. The relationship between analytics and AI is rapidly evolving.

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Implement data quality checks on Amazon Redshift data assets and integrate with Amazon DataZone

AWS Big Data

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.

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From data lakes to insights: dbt adapter for Amazon Athena now supported in dbt Cloud

AWS Big Data

At AWS, we are committed to empowering organizations with tools that streamline data analytics and transformation processes. This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience.

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Looker Simplifies Business Intelligence in the Cloud

David Menninger's Analyst Perspectives

Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance.

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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

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Visualize data quality scores and metrics generated by AWS Glue Data Quality

AWS Big Data

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

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What is a Data Mesh?

DataKitchen

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. The organizational concepts behind data mesh are summarized as follows.