AWS Big Data

AUGUST 15, 2024

Traditional data management—wherein each business unit ingests raw data in separate data lakes or warehouses—hinders visibility and cross-functional analysis. A data mesh framework empowers business units with data ownership and facilitates seamless sharing.

Data Lake 122

Data Lake Data Warehouse Data Governance Publishing 122

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 116

Data Lake Statistics Broadcasting Optimization 116

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 131

Data Lake Testing Big Data Management 131

AWS Big Data

AUGUST 9, 2023

The combination of a data lake in a serverless paradigm brings significant cost and performance benefits. Similarly, in a serverless paradigm, application logs in Amazon CloudWatch are sourced from a variety of participating services, and traversing the lineage across logs can also present challenges.

Data Lake 98

Data Lake Metrics Cost-Benefit Testing 98

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

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. However, efficiently managing and synchronizing data within these lakes presents a significant challenge.

Data Lake 116

Data Lake Marketing Data Processing Management 116

AWS Big Data

JUNE 10, 2024

Solving the small file problem and improving query performance In modern data architectures, stream processing engines such as Amazon EMR are often used to ingest continuous streams of data into data lakes using Apache Iceberg. The following table shows the cost and time for each query and product. 5 seconds $0.08

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

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 117

Data Lake Metadata Data Warehouse Data Processing 117

Jet Global

NOVEMBER 5, 2020

Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster. Unfortunately, Microsoft is not providing that kind of data warehouse solution out of the box.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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 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 98

Data Lake Snapshot Optimization Data Transformation 98

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

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

CIO Business Intelligence

FEBRUARY 27, 2025

Giving the mobile workforce access to this data via the cloud allows them to be productive from anywhere, fosters collaboration, and improves overall strategic decision-making. Connecting mainframe data to the cloud also has financial benefits as it leads to lower mainframe CPU costs by leveraging cloud computing for data transformations.

Metadata 98

Metadata Data Lake Cost-Benefit Forecasting 98

CIO Business Intelligence

DECEMBER 20, 2024

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

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. For more information, see Changing the default settings for your data lake.

Data Lake 98

Data Lake Visualization Dashboards Insurance 98

AWS Big Data

OCTOBER 23, 2024

The Airflow REST API facilitates a wide range of use cases, from centralizing and automating administrative tasks to building event-driven, data-aware data pipelines. In this post, we discuss the enhancement and present several use cases that the enhancement unlocks for your Amazon MWAA environment.

Interactive 115

Interactive Testing Data-driven Data Lake 115

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 98

Data Lake Data Governance Machine Learning Cost-Benefit 98

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

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

CIO Business Intelligence

FEBRUARY 20, 2025

Klingbeil and Ensono have seen the challenges that legacy apps present for AI firsthand. This allows for the extraction and integration of data into AI models without overhauling entire platforms, Erolin says. CIOs should also use data lakes to aggregate information from multiple sources, he adds.

Insurance 108

Insurance Cost-Benefit Unstructured Data Data Lake 108

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. Navigate to AWS CloudFormation. Choose Stacks. Select texttosqlmetadata Choose Delete.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

AWS Big Data

OCTOBER 30, 2024

Files already present at the S3 location will not be visible to the auto-copy job. 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.

Data Warehouse 111

Data Warehouse Sales Data Lake Recreation/Entertainment 111

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

AWS Big Data

MAY 29, 2024

In this post, we showcase the seamless integration of AWS analytics services with trusted identity propagation by presenting an end-to-end architecture for data access flows. Provide a database name ( tip-blog-redshift-ds-db ), which will be created in the Data Catalog by Lake Formation.

Data Lake 115

Data Lake Enterprise Management Business Intelligence 115

AWS Big Data

DECEMBER 12, 2024

These complex queries typically involve data sources from multiple business systems, requiring multilevel nested SQL or associations with numerous tables for highly sophisticated analytical tasks. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift.

Snapshot 97

Snapshot Recreation/Entertainment Experimentation Data Lake 97

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. In this physical plan, we don’t see the Exchange operation that is present in physical plan without storage partitioned join. Delta Lake highlights AWS Glue 5.0

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

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.

Snapshot 138

Snapshot Management Metadata Big Data 138

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

CIO Business Intelligence

AUGUST 9, 2024

The original proof of concept was to have one data repository ingesting data from 11 sources, including flat files and data stored via APIs on premises and in the cloud, Pruitt says. There are a lot of variables that determine what should go into the data lake and what will probably stay on premise,” Pruitt says.

Data Transformation 126

Data Transformation Machine Learning Data Lake Dashboards 126

Corinium

JUNE 6, 2019

present a significant barrier to adoption of the latest and greatest approaches. Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. In addition, the traditional challenges remain.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. From enhancing data lakes to empowering AI-driven analytics, AWS unveiled new tools and services that are set to shape the future of data and analytics.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

AWS Big Data

OCTOBER 10, 2023

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake.

Data Quality 111

Data Quality Data Governance Data Lake Testing 111

AWS Big Data

SEPTEMBER 4, 2024

The rapid adoption of software as a service (SaaS) solutions has led to data silos across various platforms, presenting challenges in consolidating insights from diverse sources. 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 109

Data Integration Data Lake Data-driven Cost-Benefit 109

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

DataKitchen

JANUARY 3, 2022

There’s a recent trend toward people creating data lake or data warehouse patterns and calling it data enablement or a data hub. DataOps expands upon this approach by focusing on the processes and workflows that create data enablement and business analytics. DataOps Process Hub.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

Cloudera

JUNE 2, 2022

Some of the more popular viral blogs and LinkedIn posts describe it as the following: A few observations on the modern stack diagram: Note the number of different boxes that are present. In the modern data stack, there is a diverse set of destinations where data needs to be delivered. This presents a unique set of challenges.

Enterprise 104

Enterprise Data Lake Data Collection Data-driven 104