Remove Data Transformation Remove Metadata Remove Workshop
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Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

These data processing and analytical services support Structured Query Language (SQL) to interact with the data. Writing SQL queries requires not just remembering the SQL syntax rules, but also knowledge of the tables metadata, which is data about table schemas, relationships among the tables, and possible column values.

Metadata 103
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Making OT-IT integration a reality with new data architectures and generative AI

CIO Business Intelligence

The data transformation imperative What Denso and other industry leaders realise is that for IT-OT convergence to be realised, and the benefits of AI unlocked, data transformation is vital. The company can also unify its knowledge base and promote search and information use that better meets its needs.

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Stream real-time data into Apache Iceberg tables in Amazon S3 using Amazon Data Firehose

AWS Big Data

To learn more about how to process Firehose records using Lambda, see Transform source data in Amazon Data Firehose. After executing your Lambda function, Firehose looks for routing information and operations in the metadata fields (in the following format) provided by your Lambda function. b64decode(record['data']).decode('utf-8')

Metadata 115
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Amazon EMR on EKS widens the performance gap: Run Apache Spark workloads 5.37 times faster and at 4.3 times lower cost

AWS Big Data

Metadata store – We use Spark’s in-memory data catalog to store metadata for TPC-DS databases and tables— spark.sql.catalogImplementation is set to the default value in-memory. To learn more and get started with EMR on EKS, try out the EMR on EKS Workshop and visit the EMR on EKS Best Practices Guide page.

Testing 101
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Improve observability across Amazon MWAA tasks

AWS Big Data

To run the scripts, refer to the Amazon MWAA analytics workshop. format(S3_BUCKET_NAME), 's3://{}/data/aggregated/green'.format(S3_BUCKET_NAME), To learn more and get hands-on experience, start with the Amazon MWAA analytics workshop and then use the scripts in the GitHub repo to gain more observability of your DAG run.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

Specifically, the system uses Amazon SageMaker Processing jobs to process the data stored in the data lake, employing the AWS SDK for Pandas (previously known as AWS Wrangler) for various data transformation operations, including cleaning, normalization, and feature engineering.

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The Modern Data Stack Explained: What The Future Holds

Alation

These help data analysts visualize key insights that can help you make better data-backed decisions. ELT Data Transformation Tools: ELT data transformation tools are used to extract, load, and transform your data. Examples of data transformation tools include dbt and dataform.