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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. 1X 1 4 16 64 G.2X 2X 2 8 32 128 G.4X

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The 10 biggest issues IT faces today

CIO Business Intelligence

Those dynamics are now reshaping the CIO agenda for 2022, forcing many IT leaders to reorganize their list of top concerns. Ever increasing demands for transformation. Indeed, the 2022 CIO Leadership Perspectives study from Evanta found that the No. Advancing data opportunities. Angel-Johnson shares that perspective. “I

IT 144
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Revolutionizing the consumer goods industry with integrated business planning

IBM Big Data Hub

Additionally, dashboards and reports were crafted based on the budget models and conducted variance analysis for specific areas. The implementation process was done in several stages, from January 2019 and until August 2022, with product profitability being added in the final phase. Al Rabie Saudi Foods Co.

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Optimize data layout by bucketing with Amazon Athena and AWS Glue to accelerate downstream queries

AWS Big Data

Alternatively, you can use AWS Glue for Apache Spark, which provides built-in support for bucketing configurations during the data transformation process. AWS Glue allows you to define bucketing parameters, such as the number of buckets and the columns to bucket on, providing an optimized data layout for efficient querying with Athena.

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DataOps Observability: Taming the Chaos (part 1)

DataKitchen

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 169
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DataOps Observability: Taming the Chaos (part 1)

DataKitchen

DataOps Observability can help you ensure that your complex data pipelines and processes are accurate and that they deliver as designed. Observability also validates that your data transformations, models, and reports are performing as expected. to monitor your data operations. without replacing staff or systems?to

Testing 130
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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 difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse.