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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

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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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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

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Accelerate your data warehouse migration to Amazon Redshift – Part 7

AWS Big Data

Tens of thousands of customers use Amazon Redshift to gain business insights from their data. With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. After you install the data extraction agent, register it in AWS SCT.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

Typically, you have multiple accounts to manage and run resources for your data pipeline. Looking at the Skewness Job per Job visualization, there was spike on November 1, 2023. Visualize and analyze with AWS Glue job observability metrics Let’s use the dashboard to make AWS Glue usage more performant. Let’s drill down into details.

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Aaand the New NiFi Champion is…

Cloudera

On May 3, 2023, Cloudera kicked off a contest called “Best in Flow” for NiFi developers to compete to build the best data pipelines. RK built some simple flows to pull streaming data into Google Cloud Storage and Snowflake. This blog is to congratulate our winner and review the top submissions.

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Preparing the foundations for Generative AI

CIO Business Intelligence

Data also needs to be sorted, annotated and labelled in order to meet the requirements of generative AI. No wonder CIO’s 2023 AI Priorities study found that data integration was the number one concern for IT leaders around generative AI integration, above security and privacy and the user experience.