AWS Big Data

NOVEMBER 26, 2024

Eventually, transactional data lakes emerged to add transactional consistency and performance of a data warehouse to the data lake. Central to a transactional data lake are open table formats (OTFs) such as Apache Hudi , Apache Iceberg , and Delta Lake , which act as a metadata layer over columnar formats.

Metadata 105

Metadata Data Lake Snapshot Data Warehouse 105

AWS Big Data

JANUARY 9, 2025

Iceberg offers distinct advantages through its metadata layer over Parquet, such as improved data management, performance optimization, and integration with various query engines. Icebergs table format separates data files from metadata files, enabling efficient data modifications without full dataset rewrites.

Metadata 111

Metadata Snapshot Cost-Benefit Optimization 111

Smart Data Collective

JULY 27, 2021

Customer relationship management (CRM) platforms are very reliant on big data. As these platforms become more widely used, some of the data resources they depend on become more stretched. CRM providers need to find ways to address the technical debt problem they are facing through new big data initiatives.

Big Data 137

Big Data Snapshot IT Dashboards 137

AWS Big Data

DECEMBER 4, 2024

Open table formats are emerging in the rapidly evolving domain of big data management, fundamentally altering the landscape of data storage and analysis. These are useful for flexible data lifecycle management. An Iceberg table’s metadata stores a history of snapshots, which are updated with each transaction.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

AWS Big Data

NOVEMBER 22, 2024

How RFS works OpenSearch and Elasticsearch snapshots are a directory tree that contains both data and metadata. The raw data for a given shard is stored in its corresponding shard sub-directory as a collection of Lucene files, which OpenSearch and Elasticsearch lightly obfuscates. source cluster containing 5 TiB (3.9

Snapshot 97

Snapshot Metadata Recreation/Entertainment Data Processing 97

AWS Big Data

NOVEMBER 20, 2024

We’re excited to announce a new feature in Amazon DataZone that offers enhanced metadata governance for your subscription approval process. With this update, domain owners can define and enforce metadata requirements for data consumers when they request access to data assets.

Metadata 94

Metadata Data Governance Metrics Marketing 94

AWS Big Data

JANUARY 15, 2025

An extract, transform, and load (ETL) process using AWS Glue is triggered once a day to extract the required data and transform it into the required format and quality, following the data product principle of data mesh architectures. From here, the metadata is published to Amazon DataZone by using AWS Glue Data Catalog.

IoT 111

IoT Machine Learning Metadata Data-driven 111

AWS Big Data

NOVEMBER 7, 2024

Amazon Q generative SQL for Amazon Redshift uses generative AI to analyze user intent, query patterns, and schema metadata to identify common SQL query patterns directly within Amazon Redshift, accelerating the query authoring process for users and reducing the time required to derive actionable data insights.

Metadata 105

Metadata Sales Data Warehouse Optimization 105

AWS Big Data

NOVEMBER 19, 2024

Solution overview By combining the powerful vector search capabilities of OpenSearch Service with the access control features provided by Amazon Cognito , this solution enables organizations to manage access controls based on custom user attributes and document metadata. If you don’t already have an AWS account, you can create one.

Management 98

Management Metadata Manufacturing Testing 98

Analytics Vidhya

SEPTEMBER 13, 2022

Introduction The purpose of a data warehouse is to combine multiple sources to generate different insights that help companies make better decisions and forecasting. It consists of historical and commutative data from single or multiple sources. Most data scientists, big data analysts, and business […].

Data Warehouse 357

Data Warehouse Forecasting Data Science Big Data 357

Smart Data Collective

AUGUST 25, 2020

Web developers utilized data to some capacity as well, but marketers rarely considered doing so. Big data has become critical to the evolution of digital marketing. Some of the benefits are detailed below: Optimizing metadata for greater reach and branding benefits. One of the most overlooked factors is metadata.

Data mining 137

Data mining Metadata Big Data ROI 137

AWS Big Data

NOVEMBER 29, 2023

The Eightfold Talent Intelligence Platform integrates with Amazon Redshift metadata security to implement visibility of data catalog listing of names of databases, schemas, tables, views, stored procedures, and functions in Amazon Redshift. This post discusses restricting listing of data catalog metadata as per the granted permissions.

Metadata 111

Metadata Data Warehouse Analytics Data Analytics 111

AWS Big Data

DECEMBER 4, 2024

Institutional Data & AI Platform architecture The Institutional Division has implemented a self-service data platform to enable the domain teams to build and manage data products autonomously. The following diagram illustrates the building blocks of the Institutional Data & AI Platform.

Metadata 105

Metadata Data Governance Data Quality Data-driven 105

AWS Big Data

NOVEMBER 11, 2024

The IAM role ARN must be the same for both the OpenSearch Servicer sink definition and the Kinesis Data Streams source definition. You can control what data gets indexed in different indexes using the index definition in the sink.

Metadata 121

Metadata Metrics Analytics Data Processing 121

AWS Big Data

NOVEMBER 19, 2024

Row type – Enable this option to display only rows that have at least one cell with authorized data. Unfiltered Table Metadata This tab displays the response of the AWS Glue API GetUnfilteredTableMetadata policies for the selected table. About the Authors Stefano Sandonà is a Senior Big Data Specialist Solution Architect at AWS.

Data Processing 97

Data Processing Metadata Publishing Testing 97

AWS Big Data

OCTOBER 29, 2024

To achieve this, they aimed to break down data silos and centralize data from various business units and countries into the BMW Cloud Data Hub (CDH). Consumer accounts : Used by data consumers to implement use cases insights and build applications tailored to their business needs.

Data Lake 107

Data Lake Sales Metadata Machine Learning 107

Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). granules) of the data collection for fast search, access, and retrieval is also important for efficient orchestration and delivery of the data that fuels AI, automation, and machine learning operations. Collect, curate, and catalog (i.e.,

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

AWS Big Data

DECEMBER 4, 2024

The following are the key components and steps in the integration process: Zero-ETL extracts and loads the data into Amazon S3 , a highly scalable object storage service. The data is also registered in the Glue Data Catalog , a metadata repository. Big Data and ETL Solutions Architect, Amazon MWAA and AWS Glue ETL expert.

Data Integration 114

Data Integration Data Lake Statistics Data-driven 114

AWS Big Data

NOVEMBER 19, 2024

Pricing and availability Amazon MWAA pricing dimensions remains unchanged, and you only pay for what you use: The environment class Metadata database storage consumed Metadata database storage pricing remains the same. The number of concurrent Airflow tasks in the worker ( worker_autoscale ) can be set to a maximum value of 3.

Metadata 111

Metadata Cost-Benefit Metrics Optimization 111

AWS Big Data

OCTOBER 30, 2024

Publish data assets – As the data producer from the retail team, you must ingest individual data assets into Amazon DataZone. For this use case, create a data source and import the technical metadata of four data assets— customers , order_items , orders , products , reviews , and shipments —from AWS Glue Data Catalog.

Visualization 119

Visualization Data Lake Testing Data Governance 119

AWS Big Data

OCTOBER 25, 2023

But most important of all, the assumed dormant value in the unstructured data is a question mark, which can only be answered after these sophisticated techniques have been applied. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. The solution integrates data in three tiers.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

AWS Big Data

MAY 29, 2024

Since its inception, Apache Kafka has depended on Apache Zookeeper for storing and replicating the metadata of Kafka brokers and topics. the Kafka community has adopted KRaft (Apache Kafka on Raft), a consensus protocol, to replace Kafka’s dependency on ZooKeeper for metadata management. For Metadata mode , select KRaft.

Metadata 112

Metadata Cost-Benefit Management Big Data 112

AWS Big Data

DECEMBER 4, 2024

SageMaker brings together widely adopted AWS ML and analytics capabilities—virtually all of the components you need for data exploration, preparation, and integration; petabyte-scale big data processing; fast SQL analytics; model development and training; governance; and generative AI development.

Data Analytics 102

Data Analytics Analytics Data Lake Data Quality 102

Rocket-Powered Data Science

MARCH 10, 2020

The training data and feature sets that feed machine learning algorithms can now be immensely enriched with tags, labels, annotations, and metadata that were inferred and/or provided naturally through the transformation of your repository of data into a graph of data.

Metadata 250

Metadata Machine Learning Prescriptive Analytics ROI 250

AWS Big Data

NOVEMBER 7, 2024

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. Amazon Redshift is a fully managed data warehouse service offered by Amazon Web Services (AWS).

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

AWS Big Data

NOVEMBER 6, 2024

reduces the Amazon DynamoDB cost associated with KCL by optimizing read operations on the DynamoDB table storing metadata. KCL uses DynamoDB to store metadata such as shard-worker mapping and checkpoints. Other benefits in KCL 3.0 In addition to the stream processing cost savings, KCL 3.0 Key checklists when you choose to use KCL 3.0

Cost-Benefit 116

Cost-Benefit Metadata Optimization Publishing 116

erwin

JANUARY 14, 2021

When the pandemic first hit, there was some negative impact on big data and analytics spending. Digital transformation was accelerated, and budgets for spending on big data and analytics increased. Technical metadata is what makes up database schema and table definitions.

Digital Transformation 143

Digital Transformation Metadata Big Data Data-driven 143

AWS Big Data

DECEMBER 16, 2024

This approach simplifies your data journey and helps you meet your security requirements. The SageMaker Lakehouse data connection testing capability boosts your confidence in established connections. About the Authors Chiho Sugimoto is a Cloud Support Engineer on the AWS Big Data Support team.

Visualization 90

Visualization Data Processing Testing Publishing 90

AWS Big Data

SEPTEMBER 12, 2024

The AWS Glue Data Catalog now enhances managed table optimization of Apache Iceberg tables by automatically removing data files that are no longer needed. Iceberg creates a new version called a snapshot for every change to the data in the table. The customer table data and metadata are stored in the S3 bucket.

Optimization 129

Optimization Snapshot Metadata Metrics 129

AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

Management 116

Management Big Data Data Warehouse Metadata 116

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. We would like to talk about data visualization and its role in the big data movement.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

AWS Big Data

APRIL 3, 2024

Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time. Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more.

Data Lake 124

Data Lake Snapshot Metadata Data Architecture 124

AWS Big Data

DECEMBER 17, 2024

We have enhanced data sharing performance with improved metadata handling, resulting in data sharing first query execution that is up to four times faster when the data sharing producers data is being updated.

Data Lake 97

Data Lake Data Warehouse Data-driven Optimization 97

AWS Big Data

JUNE 10, 2024

Apache Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for processing engines such as Apache Spark, Trino, Apache Flink, Presto, Apache Hive, and Impala to safely work with the same tables at the same time. Each change to a table produces a new metadata file to provide atomicity.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

SEPTEMBER 11, 2024

Each file arrives as a pair with a tail metadata file in CSV format containing the size and name of the file. This metadata file is later used to read source file names during processing into the staging layer. These files follow the same naming pattern, with a daily system-generated timestamp appended to each file name.

Data Architecture 110

Data Architecture Optimization Data Warehouse Metadata 110

Smart Data Collective

SEPTEMBER 26, 2021

Working with massive structured and unstructured data sets can turn out to be complicated. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. So, let’s have a close look at some of the best strategies to work with large data sets. It’s a good idea to record metadata.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

AWS Big Data

OCTOBER 21, 2024

Business analysts enhance the data with business metadata/glossaries and publish the same as data assets or data products. The data security officer sets permissions in Amazon DataZone to allow users to access the data portal. Amazon Athena is used to query, and explore the data.

Sales 115

Sales Data-driven Data Processing Key Performance Indicator 115