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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 103
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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 103
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Interact with Apache Iceberg tables using Amazon Athena and cross account fine-grained permissions using AWS Lake Formation

AWS Big Data

Register the S3 path storing the table using Lake Formation We register the S3 full path in Lake Formation: Navigate to the Lake Formation console. In the navigation pane, under Register and ingest , choose Data lake locations. Jack Ye is a software engineer of the Athena Data Lake and Storage team at AWS.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics

AWS Big Data

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. The following is a visual representation of an example job where the number of workers is 10. When the example job ran, the workerUtilization metrics showed the following trend.

Metrics 96
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Simplifying data processing at Capitec with Amazon Redshift integration for Apache Spark

AWS Big Data

The data sourcing problem To ensure the reliability of PySpark data pipelines, it’s essential to have consistent record-level data from both dimensional and fact tables stored in the Enterprise Data Warehouse (EDW). These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

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CIOs press ahead for gen AI edge — despite misgivings

CIO Business Intelligence

If anything, 2023 has proved to be a year of reckoning for businesses, and IT leaders in particular, as they attempt to come to grips with the disruptive potential of this technology — just as debates over the best path forward for AI have accelerated and regulatory uncertainty has cast a longer shadow over its outlook in the wake of these events.

Risk 137
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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. venvScriptsactivate.bat After this step, the subsequent steps run within the bounds of the virtual environment on the client machine and interact with the AWS account as needed. Let’s drill down into details.

Metrics 106