AWS Big Data

NOVEMBER 22, 2024

This integration enables data teams to efficiently transform and manage data using Athena with dbt Cloud’s robust features, enhancing the overall data workflow experience. This enables you to extract insights from your data without the complexity of managing infrastructure.

Data Lake 104

Data Lake Data Warehouse Cost-Benefit Data Transformation 104

David Menninger's Analyst Perspectives

OCTOBER 26, 2021

Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models. The platform supports streaming data, SQL queries, graph processing and machine learning.

Big Data 327

Big Data Data Processing Machine Learning Modeling 327

AWS Big Data

APRIL 8, 2025

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. Manage catalog commit conflicts Catalog commit conflicts are relatively straightforward to handle through table properties.

Snapshot 138

Snapshot Management Metadata Big Data 138

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management.

Management 324

Management Data Warehouse Data Quality Data Integration 324

Analytics Vidhya

JANUARY 2, 2023

Introduction Delta Lake is an open-source storage layer that brings data lakes to the world of Apache Spark. Delta Lakes provides an ACID transaction–compliant and cloud–native platform on top of cloud object stores such as Amazon S3, Microsoft Azure Storage, and Google Cloud Storage.

Data Lake 336

Data Lake Analytics Data Warehouse IT 336

Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. Data Type and Processing.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

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 115

Data Integration Data Lake Statistics Data-driven 115

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. This user can only query data from ADLS.

Data Lake 131

Data Lake Analytics Cost-Benefit Management 131

AWS Big Data

OCTOBER 10, 2024

Amazon Redshift has established itself as a highly scalable, fully managed cloud data warehouse trusted by tens of thousands of customers for its superior price-performance and advanced data analytics capabilities. This allows you to maintain a comprehensive view of your data while optimizing for cost-efficiency.

Data Lake 121

Data Lake Data Warehouse Recreation/Entertainment Data-driven 121

AWS Big Data

OCTOBER 30, 2024

Amazon DataZone now launched authentication supports through the Amazon Athena JDBC driver, allowing data users to seamlessly query their subscribed data lake assets via popular business intelligence (BI) and analytics tools like Tableau, Power BI, Excel, SQL Workbench, DBeaver, and more.

Visualization 119

Visualization Data Lake Testing Data Governance 119

AWS Big Data

APRIL 3, 2024

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

Data Lake 127

Data Lake Snapshot Metadata Data Architecture 127

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. Business units access clean, standardized data.

Data Lake 122

Data Lake Data Warehouse Data Governance Publishing 122

AWS Big Data

DECEMBER 17, 2024

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

AWS Big Data

OCTOBER 3, 2023

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. We will use AWS Region us-east-1.

Data Lake 122

Data Lake Metadata Snapshot Recreation/Entertainment 122

David Menninger's Analyst Perspectives

JUNE 12, 2019

Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security.

Management 270

Management Data Quality Data Integration Data Lake 270

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. and Delta Lake 2.3.0. Apache Iceberg 1.2.0,

Data Lake 130

Data Lake Metadata Statistics Optimization 130

AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure.

Data Lake 137

Data Lake Data Warehouse Visualization Snapshot 137

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 104

Data Analytics Analytics Data Lake Data Quality 104

AWS Big Data

OCTOBER 29, 2024

This led to inefficiencies in data governance and access control. AWS Lake Formation is a service that streamlines and centralizes the data lake creation and management process. The Solution: How BMW CDH solved data duplication The CDH is a company-wide data lake built on Amazon Simple Storage Service (Amazon S3).

Data Lake 109

Data Lake Sales Metadata Machine Learning 109

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 131

Data Lake Testing Big Data Management 131

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

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. However, efficiently managing and synchronizing data within these lakes presents a significant challenge.

Data Lake 116

Data Lake Marketing Data Processing Management 116

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 119

Data Lake Data Warehouse Metadata Data Architecture 119

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 137

Data Lake Data Processing Metadata Snapshot 137

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

OCTOBER 1, 2024

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries.

Data Lake 116

Data Lake Statistics Broadcasting Optimization 116

AWS Big Data

MARCH 13, 2025

Unified access to your data is provided by Amazon SageMaker Lakehouse , a unified, open, and secure data lakehouse built on Apache Iceberg open standards. To overcome these hurdles, many organizations are building bespoke integrations between services, tools, and homegrown access management systems.

Analytics 113

Analytics Data Lake Data Warehouse Data-driven 113

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

Data Lake 130

Data Lake Publishing Metadata Data-driven 130

AWS Big Data

JUNE 10, 2024

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

Data Lake 117

Data Lake Metadata Data Warehouse Data Processing 117

AWS Big Data

JUNE 10, 2024

The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data. A solution based on Apache Iceberg encompasses complete data management, featuring simple built-in table optimization capabilities within an existing storage solution.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

AUGUST 9, 2023

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. By monitoring application logs, you can gain insights into job execution, troubleshoot issues promptly to ensure the overall health and reliability of data pipelines.

Data Lake 98

Data Lake Metrics Cost-Benefit Testing 98

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. Preprocessing Lambda enables you to run code without provisioning or managing servers.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

AWS Big Data

APRIL 24, 2025

Amazon SageMaker Lakehouse now supports attribute-based access control (ABAC) with AWS Lake Formation , using AWS Identity and Access Management (IAM) principals and session tags to simplify data access, grant creation, and maintenance.

Sales 89

Sales Data Lake Management Data-driven 89

AWS Big Data

DECEMBER 20, 2024

This means you can refine your ETL jobs through natural follow-up questionsstarting with a basic data pipeline and progressively adding transformations, filters, and business logic through conversation. The DataFrame code generation now extends beyond AWS Glue DynamicFrame to support a broader range of data processing scenarios.

Data Integration 105

Data Integration Visualization Data Processing Big Data 105

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

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. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially. datazone_env_twinsimsilverdata"."cycle_end";')

IoT 111

IoT Machine Learning Metadata Data-driven 111