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 96

Snapshot Metadata Recreation/Entertainment Data Processing 96

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 93

Metadata Data Governance Metrics Marketing 93

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

DECEMBER 9, 2024

Icebergs branching feature Iceberg offers a branching feature for data lifecycle management, which is particularly useful for efficiently implementing the WAP pattern. The metadata of an Iceberg table stores a history of snapshots. He is particularly passionate about big data technologies and open source software.

Data Quality 124

Data Quality Publishing Snapshot Data Lake 124

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

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

FEBRUARY 6, 2023

Review the MongoDB AWS Glue database and table We can navigate to the AWS Glue Data Catalog to examine the tables that were created by the crawler. Choose the table to view the schema and other metadata. Note that the crawler captured nested data as a STRUCT and correctly listed the ARRAY fields.

Metadata 97

Metadata Data Lake Machine Learning Big Data 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 106

Data Lake Sales Metadata Machine Learning 106

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 113

Data Integration Data Lake Statistics Data-driven 113

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

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 115

Management Big Data Data Warehouse Metadata 115

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 111

Metadata Cost-Benefit Management Big Data 111

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 123

Data Lake Snapshot Metadata Data Architecture 123

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

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

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 115

Cost-Benefit Metadata Optimization Publishing 115

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 89

Visualization Data Processing Testing Publishing 89

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 128

Optimization Snapshot Metadata Metrics 128

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

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 96

Data Lake Data Warehouse Data-driven Optimization 96

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

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

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

AWS Big Data

DECEMBER 10, 2024

Save the federation metadata XML file You use the federation metadata file to configure the IAM IdP in a later step. In the Single sign-on section , under SAML Certificates , choose Download for Federation Metadata XML. Complete the following steps to download the file: Navigate back to your SAML-based sign-in page.

Sales 105

Sales Metadata Enterprise Testing 105

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 136

Data Lake Data Processing Metadata Snapshot 136

AWS Big Data

OCTOBER 2, 2024

Governed Tables metadata will continue to exist within the AWS Glue Data Catalog, and the Governed Tables data will remain in your S3 buckets. About the author Mert Hocanin is a Principal Big Data Architect with AWS Lake Formation. After February 17, 2025, all Governed Table APIs will start to fail.

Snapshot 122

Snapshot Metadata Big Data Analytics 122

AWS Big Data

MARCH 22, 2024

Benchmark setup In our testing, we used the 3 TB dataset stored in Amazon S3 in compressed Parquet format and metadata for databases and tables is stored in the AWS Glue Data Catalog. This benchmark uses unmodified TPC-DS data schema and table relationships. He has been focusing in the big data analytics space since 2014.

Metadata 118

Metadata Statistics Broadcasting Optimization 118