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

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 115

Data Lake Statistics Broadcasting Optimization 115

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 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

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 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 124

Data Lake Snapshot Metadata Data Architecture 124

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.

Data Lake 130

Data Lake Metadata Statistics Optimization 130

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

APRIL 24, 2025

These tags are assigned to IAM users or roles and can be used to define or restrict access to specific resources or data. For more details, refer to Tags for AWS Identity and Access Management resources and Pass session tags in AWS STS. Set up a data lake admin. For instructions, see Create a data lake administrator.

Sales 86

Sales Data Lake Management Data-driven 86

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

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 114

Data Lake Metadata Data Warehouse Data Processing 114

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

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

Jet Global

NOVEMBER 5, 2020

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. Option 3: Azure Data Lakes. This leads us to Microsoft’s apparent long-term strategy for D365 F&SCM reporting: Azure Data Lakes.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

FEBRUARY 24, 2023

Data lakes are a popular choice for today’s organizations to store their data around their business activities. As a best practice of a data lake design, data should be immutable once stored. A data lake built on AWS uses Amazon Simple Storage Service (Amazon S3) as its primary storage environment.

Data Lake 98

Data Lake Metadata Testing Data Warehouse 98

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 114

Data Integration Data Lake Statistics Data-driven 114

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

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. For more information, refer to Retry Amazon S3 requests with EMRFS. availability.

Data Lake 98

Data Lake Snapshot Metadata Optimization 98

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 99

Data Lake Testing Snapshot Big Data 99

AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. file, enter the preprocessing code for the raw lineage data.

Snapshot 96

Snapshot Recreation/Entertainment Experimentation Data Lake 96

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 97

Data Lake Snapshot Optimization Data Transformation 97

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 98

Data Lake Data Transformation Data-driven Cost-Benefit 98

AWS Big Data

NOVEMBER 14, 2024

Under the hood, UniForm generates Iceberg metadata files (including metadata and manifest files) that are required for Iceberg clients to access the underlying data files in Delta Lake tables. Both Delta Lake and Iceberg metadata files reference the same data files. in Delta Lake public document. Appendix 1.

Metadata 122

Metadata Data Warehouse Big Data Data Lake 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. He can be reached via LinkedIn.

Data Lake 128

Data Lake Big Data Cost-Benefit Data Warehouse 128

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

JULY 21, 2023

Data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts.

Data Lake 98

Data Lake Data Warehouse Marketing Management 98

AWS Big Data

JANUARY 26, 2023

AWS Glue provides an extensible architecture that enables users with different data processing use cases. A common use case is building data lakes on Amazon Simple Storage Service (Amazon S3) using AWS Glue extract, transform, and load (ETL) jobs. AWS Glue version Hudi Delta Lake Iceberg AWS Glue 3.0 AWS Glue 4.0

Data Lake 135

Data Lake Big Data Software Interactive 135

AWS Big Data

JANUARY 27, 2023

For example, the Flink FileSystem connector has FileSystemTableFactory to read/write data in Hadoop Distributed File System (HDFS) or Amazon Simple Storage Service (Amazon S3), the Flink HBase connector has HBase2DynamicTableFactory to read/write data in HBase, and the Flink Kafka connector has KafkaDynamicTableFactory to read/write data in Kafka.

Data Lake 85

Data Lake Metadata Business Analysis Data-driven 85

AWS Big Data

NOVEMBER 7, 2024

Refer to Easy analytics and cost-optimization with Amazon Redshift Serverless to get started. It can help optimize the generation process by reducing unnecessary table references. The public.set_translations table contains the data sufficient to answer the question. For this post, we use Redshift Serverless.

Metadata 105

Metadata Sales Data Warehouse Optimization 105

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.

Metadata 104

Metadata Data Lake Modeling Data Warehouse 104

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

OCTOBER 30, 2024

With this integration, you can now seamlessly query your governed data lake assets in Amazon DataZone using popular business intelligence (BI) and analytics tools, including partner solutions like Tableau. Refer to the detailed blog post on how you can use this to connect through various other tools.

Analytics 118

Analytics Visualization Data Governance Data-driven 118

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

APRIL 11, 2023

By collecting data from store sensors using AWS IoT Core , ingesting it using AWS Lambda to Amazon Aurora Serverless , and transforming it using AWS Glue from a database to an Amazon Simple Storage Service (Amazon S3) data lake, retailers can gain deep insights into their inventory and customer behavior.

Forecasting 97

Forecasting Management IoT Data-driven 97

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. For more details, refer to the BladeBridge Analyzer Demo. Amazon Redshift is built for scale and delivers up to 7.9

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

AWS Big Data

OCTOBER 30, 2024

Automate ingestion from a single data source With a auto-copy job, you can automate ingestion from a single data source by creating one job and specifying the path to the S3 objects that contain the data. The S3 object path can reference a set of folders that have the same key prefix.

Data Warehouse 108

Data Warehouse Sales Data Lake Recreation/Entertainment 108

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