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Modernize your legacy databases with AWS data lakes, Part 2: Build a data lake using AWS DMS data on Apache Iceberg

AWS Big Data

This is part two of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to load data from a legacy database (SQL Server) into a transactional data lake ( Apache Iceberg ) using AWS Glue. To start the job, choose Run. format(dbname)).config("spark.sql.catalog.glue_catalog.catalog-impl",

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The future of data: A 5-pillar approach to modern data management

CIO Business Intelligence

Manish Limaye Pillar #1: Data platform The data platform pillar comprises tools, frameworks and processing and hosting technologies that enable an organization to process large volumes of data, both in batch and streaming modes. Now, mature organizations implement cybersecurity broadly using DevSecOps practices.

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Generate vector embeddings for your data using AWS Lambda as a processor for Amazon OpenSearch Ingestion

AWS Big Data

The Lambda function will invoke the Amazon Titan Text Embeddings Model hosted in Amazon Bedrock , allowing for efficient and scalable embedding creation. This architecture simplifies various use cases, including recommendation engines, personalized chatbots, and fraud detection systems.

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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

AWS Big Data

Together with price-performance, Amazon Redshift offers capabilities such as serverless architecture, machine learning integration within your data warehouse and secure data sharing across the organization. dbt Cloud is a hosted service that helps data teams productionize dbt deployments. Choose Create.

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7 types of tech debt that could cripple your business

CIO Business Intelligence

Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time. It also anonymizes all PII so the cloud-hosted chatbot cant be fed private information.

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How To Use Airbyte, dbt-teradata, Dagster, and Teradata Vantage™ for Seamless Data Integration

Teradata

Infrastructure layout Diagram illustrating the data flow between each component of the infrastructure Prerequisites Before you embark on this integration, ensure you have the following set up: Access to a Vantage instance: If you need a test instance of Vantage, you can provision one for free Python 3.10 dbt-core dagster==1.7.9

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Centralize Apache Spark observability on Amazon EMR on EKS with external Spark History Server

AWS Big Data

Set up AWS Private CA and create a Route 53 private hosted zone Use the following code to deploy AWS Private CA and create a Route 53 private hosted zone. For detailed guidance, refer to Spark’s web UI security documentation and SHS security features. Suvojit Dasgupta is a Principal Data Architect at AWS. deploy_ssl.sh