AWS Big Data

MARCH 18, 2024

Many organizations operate data lakes spanning multiple cloud data stores. In these cases, you may want an integrated query layer to seamlessly run analytical queries across these diverse cloud stores and streamline your data analytics processes. The AWS Glue Data Catalog holds the metadata for Amazon S3 and GCS data.

Data Lake 127

Data Lake Analytics Cost-Benefit Management 127

AWS Big Data

JUNE 10, 2024

Cloudinary is a cloud-based media management platform that provides a comprehensive set of tools and services for managing, optimizing, and delivering images, videos, and other media assets on websites and mobile applications.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

AUGUST 15, 2024

Unlocking the true value of data often gets impeded by siloed information. Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. Amazon DataZone natively supports data sharing for Amazon Redshift data assets.

Data Lake 120

Data Lake Data Warehouse Data Governance Publishing 120

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 118

Data Lake Data Warehouse Metadata Data Architecture 118

AWS Big Data

MARCH 2, 2023

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. and later supports the Apache Iceberg framework for data lakes. AWS Glue 3.0 The following diagram illustrates the solution architecture.

Data Lake 136

Data Lake Data Processing Metadata Snapshot 136

AWS Big Data

APRIL 18, 2024

The Salesforce Trust Intelligence Platform (TIP) log platform team is responsible for data pipeline and data lake infrastructure, providing log ingestion, normalization, persistence, search, and detection capability to ensure Salesforce is safe from threat actors. Headquartered in San Francisco, Salesforce, Inc.

Optimization 110

Optimization Data Lake Management Key Performance Indicator 110

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. Their ability to resolve critical issues such as data consistency, query efficiency, and governance renders them indispensable for data- driven organizations.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

AWS Big Data

DECEMBER 4, 2024

With this new functionality, customers can create up-to-date replicas of their data from applications such as Salesforce, ServiceNow, and Zendesk in an Amazon SageMaker Lakehouse and Amazon Redshift. SageMaker Lakehouse gives you the flexibility to access and query your data in-place with all Apache Iceberg compatible tools and engines.

Data Integration 112

Data Integration Data Lake Statistics Data-driven 112

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 122

Data Lake Sales Data Warehouse Snapshot 122

AWS Big Data

MAY 20, 2024

Whether you are new to Apache Iceberg on AWS or already running production workloads on AWS, this comprehensive technical guide offers detailed guidance on foundational concepts to advanced optimizations to build your transactional data lake with Apache Iceberg on AWS. He can be reached via LinkedIn.

Data Lake 124

Data Lake Big Data Cost-Benefit Data Warehouse 124

AWS Big Data

SEPTEMBER 10, 2024

We often see requests from customers who have started their data journey by building data lakes on Microsoft Azure, to extend access to the data to AWS services. In such scenarios, data engineers face challenges in connecting and extracting data from storage containers on Microsoft Azure.

Data Lake 111

Data Lake Metadata Management Software 111

AWS Big Data

JULY 31, 2024

In the current industry landscape, data lakes have become a cornerstone of modern data architecture, serving as repositories for vast amounts of structured and unstructured data. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

Data Lake 116

Data Lake Marketing Data Processing Management 116

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

AUGUST 21, 2024

To address this requirement, Redshift Serverless launched the artificial intelligence (AI)-driven scaling and optimization feature, which scales the compute not only based on the queuing, but also factoring data volume and query complexity. The slider offers the following options: Optimized for cost – Prioritizes cost savings.

Optimization 104

Optimization Data Lake Data Warehouse Cost-Benefit 104

AWS Big Data

SEPTEMBER 26, 2024

For many organizations, this centralized data store follows a data lake architecture. Although data lakes provide a centralized repository, making sense of this data and extracting valuable insights can be challenging. About the Authors Dave Horne is a Sr.

Data Lake 113

Data Lake Cost-Benefit Unstructured Data Modeling 113

AWS Big Data

OCTOBER 3, 2023

In our previous post Improve operational efficiencies of Apache Iceberg tables built on Amazon S3 data lakes , we discussed how you can implement solutions to improve operational efficiencies of your Amazon Simple Storage Service (Amazon S3) data lake that is using the Apache Iceberg open table format and running on the Amazon EMR big data platform.

Optimization 126

Optimization Snapshot Data Lake Metadata 126

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Lakshmi Nair is a Senior Specialist Solutions Architect for Data Analytics at AWS. datazone_env_twinsimsilverdata"."cycle_end";') She can reached via LinkedIn.

IoT 110

IoT Machine Learning Metadata Data-driven 110

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. As more table changes are made, more data files are created.

Optimization 127

Optimization Snapshot Metadata Metrics 127

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. This property is set to true by default. availability.

Data Lake 98

Data Lake Snapshot Metadata Optimization 98

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. Unlike direct Amazon S3 access, Iceberg supports these operations on petabyte-scale data lakes without requiring complex custom code.

Metadata 111

Metadata Snapshot Cost-Benefit Optimization 111

AWS Big Data

NOVEMBER 17, 2023

You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and 30 data sources, including on-premises data sources or other cloud systems using SQL or Python. Let’s discuss some of the cost-based optimization techniques that contributed to improved query performance.

Optimization 130

Optimization Statistics Metadata Data Lake 130

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. You can add more such query optimization rules to the instructions.

Metadata 102

Metadata Data Lake Modeling Data Warehouse 102

AWS Big Data

FEBRUARY 14, 2023

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history.

Data Lake 98

Data Lake Statistics Data Architecture Finance 98

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

AWS Big Data

APRIL 27, 2023

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

Data Lake 95

Data Lake Snapshot Optimization Data Transformation 95

Jet Global

JULY 2, 2019

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

JUNE 23, 2023

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

Data Lake 91

Data Lake Dashboards Cost-Benefit Data Warehouse 91

AWS Big Data

NOVEMBER 22, 2024

Important considerations for preview As you begin using automated Spark upgrades during the preview period, there are several important aspects to consider for optimal usage of the service: Service scope and limitations – The preview release focuses on PySpark code upgrades from AWS Glue versions 2.0 to version 4.0.

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

AWS Big Data

OCTOBER 30, 2024

Users can begin ingesting data to Redshift from Amazon S3 with simple SQL commands and gain access to the most up-to-date data without the need for third-party tools or custom implementation. He has worked with building data warehouses and big data solutions for over 15+ years.

Data Warehouse 105

Data Warehouse Sales Data Lake Recreation/Entertainment 105

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

AWS Big Data

NOVEMBER 7, 2024

Tens of thousands of customers use Amazon Redshift every day to run analytics, processing exabytes of data for business insights. times better price performance than other cloud data warehouses. He has helped customers build scalable data warehousing and big data solutions for over 16 years.

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

AWS Big Data

DECEMBER 12, 2024

Amazon Athena offers serverless, flexible SQL analytics for one-time queries, enabling direct querying of Amazon Simple Storage Service (Amazon S3) data for rapid, cost-effective instant analysis. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift.

Snapshot 94

Snapshot Recreation/Entertainment Experimentation Data Lake 94

CDW Research Hub

JULY 18, 2022

One modern data platform solution that provides simplicity and flexibility to grow is Snowflake’s data cloud and platform. These Snowflake accelerators reduce the time to analytics for your users at all levels so you can make data-driven decisions faster. Security Data Lake. Optimizing Snowflake functionality.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

JUNE 15, 2023

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems.

Data Lake 105

Data Lake Metadata Cost-Benefit Management 105

Smart Data Collective

FEBRUARY 23, 2022

Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. That is when data lake products started gaining popularity, and since then, more companies introduced lake solutions as part of their data infrastructure. How to improve indexing.

Data Lake 124

Data Lake Cost-Benefit Optimization Big Data 124

AWS Big Data

JANUARY 6, 2025

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Analytics 98

Analytics Data Warehouse Big Data Metrics 98