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

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 128

Optimization Snapshot Metadata Metrics 128

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

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

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. Table metadata is fetched from AWS Glue. The generated Athena SQL query is run.

Metadata 103

Metadata Data Lake Modeling Data Warehouse 103

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

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.

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Data Lake Sales Data Warehouse Snapshot 122

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.

Data Lake 113

Data Lake Cost-Benefit Unstructured Data Modeling 113

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

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

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

Cloudera

OCTOBER 10, 2024

It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse. Let’s take a look at some of the features in Cloudera Lakehouse Optimizer, the benefits they provide, and the road ahead for this service.

Optimization 90

Optimization Snapshot Data Lake Cost-Benefit 90

AWS Big Data

FEBRUARY 6, 2023

For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to discover and catalog data in the background. This allows users to search and find relevant data from multiple data sources. Choose the table to view the schema and other metadata.

Metadata 96

Metadata Data Lake Machine Learning Big Data 96

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

AWS Big Data

NOVEMBER 21, 2024

The AWS Glue Data Catalog supports automatic table optimization of Apache Iceberg tables, including compaction , snapshots, and orphan data management. The data compaction optimizer constantly monitors table partitions and kicks off the compaction process when the threshold is exceeded for the number of files and file sizes.

Optimization 111

Optimization Snapshot Metadata Software 111

CIO Business Intelligence

DECEMBER 9, 2024

In addition to technical advancements, the event highlighted strategic initiatives that resonate with CIOs, including cost optimization, workflow efficiency, and accelerated AI application development. On the storage front, AWS unveiled S3 Table Buckets and the S3 Metadata features.

Metadata 116

Metadata Unstructured Data Data Lake Data-driven 116

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

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. It will never remove files that are still required by a non-expired snapshot.

Snapshot 126

Snapshot Data Lake Metadata Optimization 126

Smart Data Collective

AUGUST 5, 2021

What is Delta Lake? Developed at Databricks, “Delta Lake is an open-source data storage layer that runs on the existing Data Lake and is fully cooperative with Apache Spark APIs. Delta Lake uses versioned Parquet files to store data in the cloud. Advantages of using Delta Lakes.

Data Processing 143

Data Processing Metadata Broadcasting Statistics 143

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. For CoW tables, queries see the latest data committed.

Data Lake 115

Data Lake Snapshot Metadata Optimization 115

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. We have launched new RA3.large large instances.

Data Lake 78

Data Lake Data Warehouse Data-driven Optimization 78

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 131

Data Lake Analytics Dashboards Metrics 131

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

erwin

OCTOBER 8, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

AWS Big Data

NOVEMBER 29, 2023

Modernizing analytics for scale, performance, and reliability “Our migration from legacy on-premises platform to Amazon Redshift allows us to ingest data 88% faster, query data 3x faster, and load daily data to the cloud 6x faster.

Data Warehouse 128

Data Warehouse Data Lake Analytics Machine Learning 128

AWS Big Data

OCTOBER 25, 2024

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.

Statistics 105

Statistics Data Warehouse Metadata Data Lake 105

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. By providing a standardized framework for data representation, open table formats break down data silos, enhance data quality, and accelerate analytics at scale.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Not only can resources be quickly provisioned and optimized for different workloads and processing needs, but it can be done cost effectively. The Alation Data Catalog will automatically crawl and catalog metadata in your S3 bucket(s).

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

AWS Big Data

DECEMBER 20, 2024

Solution overview The basic concept of the modernization project is to create metadata-driven frameworks, which are reusable, scalable, and able to respond to the different phases of the modernization process. These phases are: data orchestration, data migration, data ingestion, data processing, and data maintenance.

Metadata 52

Metadata Data-driven Snapshot Data Lake 52

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Proprietary file formats mean no one else is invited in!

Data Warehouse 96

Data Warehouse Data Lake IT Analytics 96

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

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 90

Data Architecture Metadata Data Lake Snapshot 90

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 115

Data Lake Snapshot Big Data Data-driven 115

AWS Big Data

JUNE 7, 2023

Through their unique position in ports, at sea, and on roads, they optimize global cargo flows and create sustainable customer value. Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. An AWS Glue job (metadata exporter) runs daily on the source account.

Metadata 59

Metadata Data Lake Machine Learning Big Data 59

Cloudera

APRIL 22, 2021

Apache Ozone is one of the major innovations introduced in CDP, which provides the next generation storage architecture for Big Data applications, where data blocks are organized in storage containers for larger scale and to handle small objects. Collects and aggregates metadata from components and present cluster state.

Data Lake 104

Data Lake Cost-Benefit Testing Metadata 104

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 113

Data Integration Data Lake Statistics Data-driven 113