Remove Big Data Remove Data Transformation Remove Structured Data
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Ingest data from Google Analytics 4 and Google Sheets to Amazon Redshift using Amazon AppFlow

AWS Big Data

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

This agility accelerates EUROGATEs insight generation, keeping decision-making aligned with current data. Additionally, daily ETL transformations through AWS Glue ensure high-quality, structured data for ML, enabling efficient model training and predictive analytics. She can reached via LinkedIn.

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Transforming Big Data into Actionable Intelligence

Sisense

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

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Enriching metadata for accurate text-to-SQL generation for Amazon Athena

AWS Big Data

Amazon Athena provides interactive analytics service for analyzing the data in Amazon Simple Storage Service (Amazon S3). Amazon Redshift is used to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes.

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Apply fine-grained access and transformation on the SUPER data type in Amazon Redshift

AWS Big Data

Amazon Redshift, a cloud data warehouse service, supports attaching dynamic data masking (DDM) policies to paths of SUPER data type columns, and uses the OBJECT_TRANSFORM function with the SUPER data type. SUPER data type columns in Amazon Redshift contain semi-structured data like JSON documents.

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Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

AWS Big Data

Spark SQL is an Apache Spark module for structured data processing. To run HiveQL-based data workloads with Spark on Kubernetes mode, engineers must embed their SQL queries into programmatic code such as PySpark, which requires additional effort to manually change code. Amazon EMR on EKS release 6.7.0

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users. Dig into AI.