AWS Big Data

JANUARY 17, 2024

Incremental query refers to a query strategy that focuses on processing and analyzing only the new or updated data within a data lake since the last query. The key idea behind incremental queries is to use metadata or change tracking mechanisms to identify the new or modified data since the last query.

Data Lake 92

Data Lake Snapshot Big Data Data-driven 92

Cloudera

MAY 22, 2018

With Experiments, data scientists can run a batch job that will: create a snapshot of model code, dependencies, and configuration parameters necessary to train the model. Furthermore, keeping track of or rolling back deployed models poses significant version control challenges for data scientists and compliance offers alike.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time. These tables are created as Iceberg tables.

Snapshot 88

Snapshot Metadata Cost-Benefit Data Warehouse 88

AWS Big Data

NOVEMBER 22, 2023

Many AWS customers adopted Apache Hudi on their data lakes built on top of Amazon S3 using AWS Glue , a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development.

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists.

Snapshot 105

Snapshot Metadata Cost-Benefit Data Architecture 105

AWS Big Data

MAY 24, 2023

Some of the important non-functional use cases for an S3 data lake that organizations are focusing on include storage cost optimizations, capabilities for disaster recovery and business continuity, cross-account and multi-Region access to the data lake, and handling increased Amazon S3 request rates. write.tags.write-tag-name and s3.delete.tags.delete-tag-name

Data Lake 81

Data Lake Snapshot Metadata Optimization 81

AWS Big Data

AUGUST 23, 2023

SS4O is inspired by both OpenTelemetry and the Elastic Common Schema (ECS) and uses Amazon Elastic Container Service ( Amazon ECS ) event logs and OpenTelemetry (OTel) metadata. in OpenSearch Service has brought new features to manage data streams and indexes on the OpenSearch Dashboards UI. in OpenSearch Service). and OpenSearch 2.7

Snapshot 93

Snapshot Dashboards Visualization Metrics 93

AWS Big Data

SEPTEMBER 13, 2023

The File Manager Lambda function consumes those messages, parses the metadata, and inserts the metadata to the DynamoDB table odpf_file_tracker. We use the following terminology when discussing File Processor: Refresh cadence – This represents the data ingestion frequency (for example, 10 minutes).

Data Lake 90

Data Lake Data Processing Metadata Snapshot 90

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. Why did Orca choose Apache Iceberg?

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

IBM Big Data Hub

JUNE 7, 2023

IBM Storage Defender is designed to be able to leverage sensors—like real-time threat detection built into IBM Storage FlashSystem —across primary and secondary workloads to detect threats and anomalies from backup metadata, array snapshots and other relevant threat indicators.

Snapshot 84

Snapshot Metadata Enterprise Testing 84

O'Reilly on Data

MARCH 20, 2019

Distributed systems and models : For better or worse, we live in the age of big data. Many organizations are now using distributed data processing and machine learning systems. Distributed computing can provide a broad attack surface for a malicious internal or external actor in the context of machine learning.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 80

Data Lake Dashboards Metrics Metadata 80

AWS Big Data

NOVEMBER 29, 2023

Complete the following steps: On the Athena console, switch the workgroup to athena-dbt-glue-aws-blog. If the workgroup athena-dbt-glue-aws-blog settings dialog box appears, choose Acknowledge. You learned the end-to-end operations and data flow for data engineers to build and manage a data stack using dbt and the dbt-glue adapter.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102