article thumbnail

Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

article thumbnail

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.

Data Lake 111
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Accelerate analytics on Amazon OpenSearch Service with AWS Glue through its native connector

AWS Big Data

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless. The following diagram illustrates the solution architecture.

article thumbnail

Measure performance of AWS Glue Data Quality for ETL pipelines

AWS Big Data

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. On the AWS Glue console, under ETL jobs in the navigation pane, choose Visual ETL. In the Create job section, choose Visual ETL.x

article thumbnail

Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

AWS Big Data

For sales across multiple markets, the product sales data such as orders, transactions, and shipment data is available on Amazon S3 in the data lake. The data engineering team can use Apache Spark with Amazon EMR or AWS Glue to analyze this data in Amazon S3. enableHiveSupport().getOrCreate()

article thumbnail

Themes and Conferences per Pacoid, Episode 8

Domino Data Lab

Somehow, the gravity of the data has a geological effect that forms data lakes. Also, data science workflows begin to create feedback loops from the big data side of the illo above over to the DW side. DG emerges for the big data side of the world, e.g., the Alation launch in 2012.

article thumbnail

Generate security insights from Amazon Security Lake data using Amazon OpenSearch Ingestion

AWS Big Data

Optionally, specify the Amazon S3 storage class for the data in Amazon Security Lake. For more information, refer to Lifecycle management in Security Lake. Review the details and create the data lake. Choose Next. Choose Component templates to verify the OCSF component templates.