Remove 2022 Remove Big Data Remove Dashboards Remove Metadata
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How Fujitsu implemented a global data mesh architecture and democratized data

AWS Big Data

To achieve data-driven management, we built OneData, a data utilization platform used in the four global AWS Regions, which started operation in April 2022. The platform consists of approximately 370 dashboards, 360 tables registered in the data catalog, and 40 linked systems.

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

Bayerische Motoren Werke AG (BMW) is a motor vehicle manufacturer headquartered in Germany with 149,475 employees worldwide and the profit before tax in the financial year 2022 was € 23.5 The CLEA dashboards were built on the foundation of the Well-Architected Lab. billion on revenues amounting to € 142.6

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AWS Professional Services scales by improving performance and democratizing data with Amazon QuickSight

AWS Big Data

In this post, we discuss how QuickSight has helped us improve our performance, democratize our data, and provide insights to our internal customers at scale. One of our ProServe teams has 19 dashboards on QuickSight, including Catalog, Trend and Analysis, KPI Monitoring, Business Management, and Quality Control.

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AI Governance: Break open the black box

IBM Big Data Hub

Furthermore, 59% of executives claim AI can improve the use of big data in their organizations, facts about artificial intelligence show. ( IBM Global AI Adoption Index 2022.). This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. What is stopping AI adoption today?

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Near-real-time analytics using Amazon Redshift streaming ingestion with Amazon Kinesis Data Streams and Amazon DynamoDB

AWS Big Data

As shown in the following reference architecture, DynamoDB table data changes are streamed into Amazon Redshift through Kinesis Data Streams and Amazon Redshift streaming ingestion for near-real-time analytics dashboard visualization using Amazon QuickSight. Prerequisites You must have the following: An AWS account.

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In 2022, AWS commissioned a study conducted by the American Productivity and Quality Center (APQC) to quantify the Business Value of Customer 360.