AWS Big Data

APRIL 30, 2024

Today, we’re excited to announce general availability of Amazon Q data integration in AWS Glue. Amazon Q data integration, a new generative AI-powered capability of Amazon Q Developer , enables you to build data integration pipelines using natural language.

Data Integration 128

Data Integration Data Lake Data Warehouse Software 128

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 122

Data Lake Data Warehouse Publishing Data Governance 122

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 105

Data Analytics Analytics Data Lake Data Quality 105

AWS Big Data

SEPTEMBER 4, 2024

Effective data analytics relies on seamlessly integrating data from disparate systems through identifying, gathering, cleansing, and combining relevant data into a unified format. This solution also allows you to update certain fields of the account object in the data lake and push it back to Salesforce.

Data Integration 110

Data Integration Data Lake Data-driven Cost-Benefit 110

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

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 119

Data Lake Data Warehouse Metadata Data Architecture 119

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

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. Now, theyre able to build and collaborate with their data and tools available in one experience, dramatically reducing time-to-value.

Analytics 114

Analytics Data Lake Data Warehouse Data-driven 114

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

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. The following table shows the cost and time for each query and product.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

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

JANUARY 15, 2025

cycle_end"', "sagemakedatalakeenvironment_sub_db", ctas_approach=False) A similar approach is used to connect to shared data from Amazon Redshift, which is also shared using Amazon DataZone. While real-time data is processed by other applications, this setup maintains high-performance analytics without the expense of continuous processing.

IoT 111

IoT Machine Learning Metadata Data-driven 111

IBM Big Data Hub

JUNE 26, 2020

Like oil, data is valuable but it must be refined in order to provide value. Organizations need to collect, organize, and analyze their data across multi-cloud, hybrid cloud, and data lakes. Yet traditional ETL tools support only a limited number of delivery styles and involve a significant amount of hand-coding.

Data Integration 107

Data Integration Data Lake Machine Learning Enterprise 107

AWS Big Data

DECEMBER 16, 2024

Third, some services require you to set up and manage compute resources used for federated connectivity, and capabilities like connection testing and data preview arent available in all services. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity.

Visualization 95

Visualization Data Processing Testing Publishing 95

AWS Big Data

JULY 10, 2024

Now you can author data preparation transformations and edit them with the AWS Glue Studio visual editor. The AWS Glue Studio visual editor is a graphical interface that enables you to create, run, and monitor data integration jobs in AWS Glue. She is passionate about helping customers build data lakes using ETL workloads.

Interactive 116

Interactive Visualization Data Integration Statistics 116

AWS Big Data

JANUARY 26, 2023

AWS Glue is a serverless, scalable data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources. AWS Glue provides an extensible architecture that enables users with different data processing use cases.

Data Lake 136

Data Lake Big Data Software Interactive 136

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

AUGUST 3, 2023

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. Apache Hudi connector for AWS Glue For this post, we use AWS Glue 4.0,

Data Lake 98

Data Lake Visualization Dashboards Insurance 98

AWS Big Data

NOVEMBER 22, 2024

About the Authors Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. Keerthi Chadalavada is a Senior Software Development Engineer at AWS Glue, focusing on combining generative AI and data integration technologies to design and build comprehensive solutions for customers’ data and analytics needs.

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

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

Data Virtualization

NOVEMBER 3, 2022

Reading Time: 4 minutes The amount of expanding volume and variety of data originating from various sources are a massive challenge for businesses. In attempts to overcome their big data challenges, organizations are exploring data lakes as repositories where huge volumes and varieties of.

Data Lake 52

Data Lake Big Data Data Integration Management 52

AWS Big Data

NOVEMBER 29, 2024

Customers often want to augment and enrich SAP source data with other non-SAP source data. Such analytic use cases can be enabled by building a data warehouse or data lake. Customers can now use the AWS Glue SAP OData connector to extract data from SAP. For more information see AWS Glue.

Visualization 105

Visualization Data Processing Data-driven Cost-Benefit 105

Juice Analytics

MAY 11, 2020

Among all the hot analytics initiatives to choose from (big data, IoT, NLP, data storytelling, cognitive BI, GDPR), plain old reporting is what is considered the most important strategic initiative. But seriously, reporting?

Reporting 134

Reporting Analytics IT Data Lake 134

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

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 111

Data Lake Big Data Data Warehouse Consulting 111

Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. A point of data entry in a given pipeline. Data Pipeline: Use Cases. Destination.

Data Warehouse 145

Data Warehouse Data Lake Visualization Big Data 145

AWS Big Data

JANUARY 9, 2025

These features allow efficient data corrections, gap-filling in time series, and historical data updates without disrupting ongoing analyses or compromising data integrity. 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

DECEMBER 15, 2023

Even after identification, it’s cumbersome to implement redaction, masking, or encryption of sensitive data at scale. In this post, we provide an automated solution to detect PII data in Amazon Redshift using AWS Glue. For our solution, we use Amazon Redshift to store the data.

Data Warehouse 119

Data Warehouse Data Lake Big Data Structured Data 119

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 116

Data Lake Data Warehouse Data-driven Optimization 116

AWS Big Data

NOVEMBER 11, 2024

Sesha Sanjana Mylavarapu is an Associate Data Lake Consultant at AWS Professional Services. She specializes in cloud-based data management and collaborates with enterprise clients to design and implement scalable data lakes.

Snapshot 111

Snapshot Strategy Dashboards Data Lake 111

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. Under Administration , choose Data catalog settings.

Data Lake 116

Data Lake Snapshot Metadata Optimization 116

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

AWS Big Data

MARCH 20, 2023

In the first post of this series , we described how AWS Glue for Apache Spark works with Apache Hudi, Linux Foundation Delta Lake, and Apache Iceberg datasets tables using the native support of those data lake formats. Even without prior experience using Hudi, Delta Lake or Iceberg, you can easily achieve typical use cases.

Visualization 98

Visualization Data Lake Snapshot Big Data 98

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 122

Data Lake Cost-Benefit Data-driven Data Warehouse 122

AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing. For more information on AWS Glue, visit AWS Glue.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

AWS Big Data

MAY 9, 2023

Hundreds of thousands of customers use AWS Glue , a serverless data integration service, to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue for Apache Spark jobs work with your code and configuration of the number of data processing units (DPU).

Data Lake 111

Data Lake Cost-Benefit Data Integration Data Transformation 111