Remove Data Transformation Remove Management Remove Metadata Remove Snapshot
article thumbnail

Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Organizations with legacy, on-premises, near-real-time analytics solutions typically rely on self-managed relational databases as their data store for analytics workloads. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

article thumbnail

Enforce fine-grained access control on Open Table Formats via Amazon EMR integrated with AWS Lake Formation

AWS Big Data

Additionally, with version 6.15, Amazon EMR introduces access control protection for its application web interface such as on-cluster Spark History Server, Yarn Timeline Server, and Yarn Resource Manager UI. The following are some highlighted steps: Run a snapshot query. %%sql Make sure you are in the us-east-1 Region.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

Moreover, running advanced analytics and ML on disparate data sources proved challenging. To overcome these issues, Orca decided to build a data lake. By decoupling storage and compute, data lakes promote cost-effective storage and processing of big data. This ensures that the data is suitable for training purposes.

article thumbnail

Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Let’s refer to this S3 bucket as the raw layer.

article thumbnail

Build and manage your modern data stack using dbt and AWS Glue through dbt-glue, the new “trusted” dbt adapter

AWS Big Data

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 100
article thumbnail

Build a data lake with Apache Flink on Amazon EMR

AWS Big Data

The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos. Apache Flink is a widely used data processing engine for scalable streaming ETL, analytics, and event-driven applications. Apache Hudi also has its own catalog management.

article thumbnail

“You Complete Me,” said Data Lineage to DataOps Observability.

DataKitchen

Data lineage and a data catalog are better together because they provide a more complete and accurate view of the data. Data lineage provides information about the origin, history, and movement of data, while runtime operations provide information about the actions performed on data while it is being processed.

Testing 130