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 120

Data Lake Data Warehouse Data Governance Publishing 120

AWS Big Data

AUGUST 21, 2024

To address this requirement, Redshift Serverless launched the artificial intelligence (AI)-driven scaling and optimization feature, which scales the compute not only based on the queuing, but also factoring data volume and query complexity. The slider offers the following options: Optimized for cost – Prioritizes cost savings.

Optimization 106

Optimization Data Lake Data Warehouse Cost-Benefit 106

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

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

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 125

Optimization Snapshot Data Lake Metadata 125

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 109

Data Lake Data Processing Metadata Snapshot 109

AWS Big Data

NOVEMBER 7, 2024

With Amazon Q, you can spend less time worrying about the nuances of SQL syntax and optimizations, allowing you to concentrate your efforts on extracting invaluable business insights from your data. Refer to Easy analytics and cost-optimization with Amazon Redshift Serverless to get started.

Metadata 104

Metadata Sales Data Warehouse Optimization 104

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. The following image is the architecture diagram for the solution.

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Snapshot Recreation/Entertainment Experimentation Data Lake 97

AWS Big Data

APRIL 24, 2025

Bob now knows that he can quickly build Amazon QuickSight dashboards with queries that are optimized using Redshifts cost-based optimizer. These tags are assigned to IAM users or roles and can be used to define or restrict access to specific resources or data. Set up a data lake admin. Choose Grant.

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 109

Data Lake Metadata Management Software 109

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 113

Data Lake Marketing Data Processing Management 113

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 109

Metadata Snapshot Cost-Benefit Optimization 109

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

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

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 112

Data Integration Data Lake Statistics Data-driven 112

AWS Big Data

MAY 20, 2025

These prompts will receive precise data from the customer databases for accounts, investments, loans, and transactions. Amazon Bedrock Knowledge Bases automatically translates these natural language queries into optimized SQL statements, thereby accelerating time to insight, enabling faster discoveries and efficient decision-making.

Structured Data 101

Structured Data Data Warehouse Analytics Finance 101

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

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

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.

Data Lake 129

Data Lake Big Data Cost-Benefit Data Warehouse 129

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 103

Metadata Data Lake Modeling Data Warehouse 103

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. Use case Amazon DataZone addresses your data sharing challenges and optimizes data availability.

Analytics 116

Analytics Visualization Data Governance Data-driven 116

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

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.

Data Lake 98

Data Lake Data Transformation Data-driven Cost-Benefit 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 128

Optimization Statistics Metadata Data Lake 128

Jet Global

SEPTEMBER 4, 2020

Its solution was to replicate data from the production database, using data entities, into a traditional relational database. Microsoft referred to this approach as “bring your own database” (BYOD). Data Lakes. There has been a lot of talk over the past year or two in the D365F&SCM world about “data lakes.”

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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 104

Data Warehouse Reporting Big Data Data Lake 104

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. We will also cover the pattern with automatic compaction through AWS Glue Data Catalog table optimization.

Snapshot 137

Snapshot Management Metadata Big Data 137

AWS Big Data

APRIL 11, 2023

Accurately predicting demand for products allows businesses to optimize inventory levels, minimize stockouts, and reduce holding costs. Solution overview In today’s highly competitive business landscape, it’s essential for retailers to optimize their inventory management processes to maximize profitability and improve customer satisfaction.

Forecasting 98

Forecasting Management IoT Data-driven 98

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

O'Reilly on Data

OCTOBER 19, 2021

but to reference concrete tooling used today in order to ground what could otherwise be a somewhat abstract exercise. Adapted from the book Effective Data Science Infrastructure. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses.

IT 364

IT Testing Experimentation Software 364

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 104

Data Lake Metadata Cost-Benefit Management 104

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. For more information, refer to Amazon S3: Allows read and write access to objects in an S3 Bucket.

Snapshot 125

Snapshot Data Lake Metadata Optimization 125

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 130

Data Lake Analytics Dashboards Metrics 130

AWS Big Data

JUNE 20, 2023

It manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Solution overview Data scientists are generally accustomed to working with large datasets.

Data Lake 101

Data Lake Data Science Recreation/Entertainment Data-driven 101

Smart Data Collective

FEBRUARY 23, 2022

Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. That is when data lake products started gaining popularity, and since then, more companies introduced lake solutions as part of their data infrastructure. How to improve indexing.

Data Lake 124

Data Lake Cost-Benefit Optimization Big Data 124

AWS Big Data

JANUARY 18, 2024

AWS Lake Formation and the AWS Glue Data Catalog form an integral part of a data governance solution for data lakes built on Amazon Simple Storage Service (Amazon S3) with multiple AWS analytics services integrating with them. To learn more about DataZone, refer to the User Guide. Bienvenue dans DataZone!

Data Lake 116

Data Lake Metadata Data Governance Statistics 116

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 111

Data Lake Data Warehouse Data-driven Optimization 111