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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. source_s3_bucket – The raw S3 bucket name. S3FileIO").getOrCreate()

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Incremental refresh for Amazon Redshift materialized views on data lake tables

AWS Big Data

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it cost-effective to analyze your data using standard SQL and business intelligence tools. One such optimization for reducing query runtime is to precompute query results in the form of a materialized view.

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From data lakes to insights: dbt adapter for Amazon Athena now supported in dbt Cloud

AWS Big Data

This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience. This enables you to extract insights from your data without the complexity of managing infrastructure.

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What is data architecture? A framework to manage data

CIO Business Intelligence

Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects. Cloud computing.

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The Unexpected Cost of Data Copies

An organization’s data is copied for many reasons, namely ingesting datasets into data warehouses, creating performance-optimized copies, and building BI extracts for analysis. Read this whitepaper to learn: Why organizations frequently end up with unnecessary data copies.

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Manage concurrent write conflicts in Apache Iceberg on the AWS Glue Data Catalog

AWS Big Data

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. We will also cover the pattern with automatic compaction through AWS Glue Data Catalog table optimization.

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Drug Launch Case Study: Amazing Efficiency Using DataOps

DataKitchen

The company focused on delivering small increments of customer value data sets, reports, and other items as their guiding principle. Small, manageable increments marked the projects delivery cadence. They opted for Snowflake, a cloud-native data platform ideal for SQL-based analysis. See the graph below.