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 121

Data Lake Data Warehouse Data Governance Publishing 121

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 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 107

Data Integration Data Lake Data-driven Cost-Benefit 107

AWS Big Data

DECEMBER 4, 2024

SageMaker still includes all the existing ML and AI capabilities you’ve come to know and love for data wrangling, human-in-the-loop data labeling with Amazon SageMaker Ground Truth , experiments, MLOps, Amazon SageMaker HyperPod managed distributed training, and more. The tools to transform your business are here.

Data Analytics 102

Data Analytics Analytics Data Lake Data Quality 102

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

CIO Business Intelligence

APRIL 25, 2024

For instance, a Data Cloud-triggered flow could update an account manager in Slack when shipments in an external data lake are marked as delayed. Sharing Customer 360 insights back without data replication. With zero-copy support, the insurance company wouldn’t have to load that weather data into their platform.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

AWS Big Data

JUNE 10, 2024

For detailed information on managing your Apache Hive metastore using Lake Formation permissions, refer to Query your Apache Hive metastore with AWS Lake Formation permissions. In this post, we present a methodology for deploying a data mesh consisting of multiple Hive data warehouses across EMR clusters.

Data Lake 113

Data Lake Metadata Data Warehouse Data Processing 113

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. AWS Glue version Hudi Delta Lake Iceberg AWS Glue 3.0

Data Lake 135

Data Lake Big Data Software Interactive 135

AWS Big Data

NOVEMBER 11, 2024

We refer to this role as TheSnapshotRole in this post. For instructions, refer to the earlier section in this post. For instructions, refer to the earlier section in this post. Sesha Sanjana Mylavarapu is an Associate Data Lake Consultant at AWS Professional Services.

Snapshot 110

Snapshot Strategy Dashboards Data Lake 110

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.

Data Lake 98

Data Lake Visualization Dashboards Insurance 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

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

David Menninger's Analyst Perspectives

OCTOBER 7, 2021

In this post, I don’t want to debate the meanings and origins of different terms; rather, I’d like to highlight a technology weapon that you should have in your data management arsenal. We currently refer to this technology as data virtualization.

Technology 246

Technology Management Data Lake IT 246

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

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 110

Data Lake Data Warehouse Data-driven Optimization 110

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 89

Visualization Data Processing Testing Publishing 89

AWS Big Data

JANUARY 12, 2024

Ingestion: Data lake batch, micro-batch, and streaming Many organizations land their source data into their data lake in various ways, including batch, micro-batch, and streaming jobs. Amazon AppFlow can be used to transfer data from different SaaS applications to a data lake.

Data Lake 119

Data Lake Cost-Benefit Visualization Structured Data 119

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 110

Data Lake Big Data Data Warehouse Consulting 110

AWS Big Data

AUGUST 22, 2024

The infrastructure provides an analytics experience to hundreds of in-house analysts, data scientists, and student-facing frontend specialists. The data engineering team is on a mission to modernize its data integration platform to be agile, adaptive, and straightforward to use.

Data Warehouse 116

Data Warehouse Data Lake Data Integration Management 116

David Menninger's Analyst Perspectives

OCTOBER 24, 2024

Although the terms data fabric and data mesh are often used interchangeably, I previously explained that they are distinct but complementary. With Denodo Platform 9, the company also added enhanced federated governance support to enable the creation, management and reuse of data products by different business units and teams.

Management 130

Management Data-driven Data Governance Data Lake 130

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

Data Lake 98

Data Lake Data Analytics Analytics Data Processing 98

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 145

Data Warehouse Data Lake Visualization Big Data 145

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. To create an AWS HealthLake data store, refer to Getting started with AWS HealthLake. reference", SUBSTRING(a."patient"."reference",

Data Analytics 118

Data Analytics Analytics Data Warehouse Data Lake 118

AWS Big Data

NOVEMBER 29, 2023

For more information about performance improvement capabilities, refer to the list of announcements below. Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications.

Data Warehouse 128

Data Warehouse Analytics Data Lake Machine Learning 128

AWS Big Data

NOVEMBER 20, 2023

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. For instructions, refer to Create a CloudWatch alarm based on a static threshold.

Metrics 125

Metrics Data Lake Cost-Benefit Dashboards 125

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 123

Data Governance Unstructured Data Metadata Data Lake 123

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. Choose Create connection. Choose Next.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

AWS Big Data

FEBRUARY 7, 2023

This post focuses on such schema changes in file-based tables and shows how to automatically replicate the schema evolution of structured data from table formats in databases to the tables stored as files in cost-effective way. Apache Hudi supports ACID transactions and CRUD operations on a data lake. and save it.

Data Lake 96

Data Lake Testing Big Data Structured Data 96

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

AWS Big Data

NOVEMBER 10, 2023

The data sourcing problem To ensure the reliability of PySpark data pipelines, it’s essential to have consistent record-level data from both dimensional and fact tables stored in the Enterprise Data Warehouse (EDW). These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

Data Processing 111

Data Processing Data Lake Data Warehouse Optimization 111

David Menninger's Analyst Perspectives

NOVEMBER 21, 2018

Once again I attended Tableau's Users Conference, along with 17,000 other attendees, affectionately self-referred to as "data nerds".

Data Lake 160

Data Lake Data Integration Data Governance Software 160

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. For more details, refer to Spark Release 3.3.0 AWS Glue Data Catalog client 3.6.0

Testing 103

Testing Data Lake Cost-Benefit Data Integration 103

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 111

Analytics IT Data Lake Visualization 111

AWS Big Data

NOVEMBER 20, 2023

In AWS, hundreds of thousands of customers use AWS Glue , a serverless data integration service, to discover, combine, and prepare data for analytics and machine learning. For more information about Apache Spark UI, refer to Web UI in Apache Spark. For more information, refer to Data Catalog and crawlers in AWS Glue.

Visualization 116

Visualization Optimization Data Lake Management 116

AWS Big Data

NOVEMBER 30, 2023

In this post, we explore how to use the AWS Glue native connector for Teradata Vantage to streamline data integrations and unlock the full potential of your data. Businesses often rely on Amazon Simple Storage Service (Amazon S3) for storing large amounts of data from various data sources in a cost-effective and secure manner.

IT 115

IT Visualization Machine Learning Data Integration 115

DataKitchen

DECEMBER 9, 2022

The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes. ChatGPT> DataOps is a term that refers to the set of practices and tools that organizations use to improve the quality and speed of data analytics and machine learning.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130