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Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore federation

AWS Big Data

One of the key challenges in modern big data management is facilitating efficient data sharing and access control across multiple EMR clusters. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. Test access using SageMaker Studio in the consumer account.

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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.

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Accelerate your data warehouse migration to Amazon Redshift – Part 7

AWS Big Data

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

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Query your Apache Hive metastore with AWS Lake Formation permissions

AWS Big Data

Apache Hive is a SQL-based data warehouse system for processing highly distributed datasets on the Apache Hadoop platform. The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table.

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Set up advanced rules to validate quality of multiple datasets with AWS Glue Data Quality

AWS Big Data

It supports both data quality at rest and data quality in AWS Glue extract, transform, and load (ETL) pipelines. Data quality at rest focuses on validating the data stored in data lakes, databases, or data warehouses. The extracted data is stored in Amazon S3, which serves as the data lake.

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Governing data in relational databases using Amazon DataZone

AWS Big Data

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

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Get Your Analytics Insights Instantly – Without Abandoning Central IT

Cloudera

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).