AWS Big Data

OCTOBER 3, 2023

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 122

Data Lake Metadata Snapshot Recreation/Entertainment 122

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. 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.

Data Lake 137

Data Lake Data Processing Metadata Snapshot 137

AWS Big Data

DECEMBER 9, 2024

Given the importance of data in the world today, organizations face the dual challenges of managing large-scale, continuously incoming data while vetting its quality and reliability. AWS Glue is a serverless data integration service that you can use to effectively monitor and manage data quality through AWS Glue Data Quality.

Data Quality 126

Data Quality Publishing Snapshot Data Lake 126

AWS Big Data

NOVEMBER 14, 2024

The landscape of big data management has been transformed by the rising popularity of open table formats such as Apache Iceberg, Apache Hudi, and Linux Foundation Delta Lake. These formats, designed to address the limitations of traditional data storage systems, have become essential in modern data architectures.

Metadata 122

Metadata Data Warehouse Big Data Data Lake 122

David Menninger's Analyst Perspectives

SEPTEMBER 28, 2021

Collibra is a data governance software company that offers tools for metadata management and data cataloging. The software enables organizations to find data quickly, identify its source and assure its integrity.

Data Governance 349

Data Governance Metadata Software Management 349

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 115

Data Integration Data Lake Statistics Data-driven 115

CIO Business Intelligence

FEBRUARY 27, 2025

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Mainframes hold an enormous amount of critical and sensitive business data including transactional information, healthcare records, customer data, and inventory metrics.

Metadata 98

Metadata Data Lake Cost-Benefit Forecasting 98

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. and Delta Lake 2.3.0. Apache Iceberg 1.2.0,

Data Lake 130

Data Lake Metadata Statistics Optimization 130

AWS Big Data

JUNE 10, 2024

The open table format accelerates companies’ adoption of a modern data strategy because it allows them to use various tools on top of a single copy of the data. A solution based on Apache Iceberg encompasses complete data management, featuring simple built-in table optimization capabilities within an existing storage solution.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

MARCH 18, 2024

Many organizations operate data lakes spanning multiple cloud data stores. In these cases, you may want an integrated query layer to seamlessly run analytical queries across these diverse cloud stores and streamline your data analytics processes. The AWS Glue Data Catalog holds the metadata for Amazon S3 and GCS data.

Data Lake 131

Data Lake Analytics Cost-Benefit Management 131

AWS Big Data

JULY 18, 2024

Over the years, organizations have invested in creating purpose-built, cloud-based data lakes that are siloed from one another. A major challenge is enabling cross-organization discovery and access to data across these multiple data lakes, each built on different technology stacks.

Data Lake 130

Data Lake Publishing Metadata Data-driven 130

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially. This process is shown in the following figure.

IoT 111

IoT Machine Learning Metadata Data-driven 111

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

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 119

Data Lake Data Warehouse Metadata Data Architecture 119

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. Business units access clean, standardized data.

Data Lake 122

Data Lake Data Warehouse Data Governance Publishing 122

AWS Big Data

DECEMBER 4, 2024

Ask questions in plain English to find the right datasets, automatically generate SQL queries, or create data pipelines without writing code. This innovation drives an important change: you’ll no longer have to copy or move data between data lake and data warehouses. Having confidence in your data is key.

Data Analytics 104

Data Analytics Analytics Data Lake Data Quality 104

AWS Big Data

JUNE 10, 2024

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

Data Lake 117

Data Lake Metadata Data Warehouse Data Processing 117

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.

Data Lake 122

Data Lake Sales Data Warehouse Snapshot 122

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. The power of the data lake lies in the fact that it often is a cost-effective way to store data.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

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

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. Their ability to resolve critical issues such as data consistency, query efficiency, and governance renders them indispensable for data- driven organizations.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

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. Preprocessing Lambda enables you to run code without provisioning or managing servers.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

AWS Big Data

NOVEMBER 7, 2024

Amazon Redshift is a fully managed, AI-powered cloud data warehouse that delivers the best price-performance for your analytics workloads at any scale. It enables you to get insights faster without extensive knowledge of your organization’s complex database schema and metadata. Your data is not shared across accounts.

Metadata 105

Metadata Sales Data Warehouse Optimization 105

CIO Business Intelligence

MAY 24, 2022

Just after launching a focused data management platform for retail customers in March, enterprise data management vendor Informatica has now released two more industry-specific versions of its Intelligent Data Management Cloud (IDMC) — one for financial services, and the other for health and life sciences.

Finance 140

Finance Management Metadata Machine Learning 140

CIO Business Intelligence

JUNE 9, 2022

A data management platform (DMP) is a group of tools designed to help organizations collect and manage data from a wide array of sources and to create reports that help explain what is happening in those data streams. Deploying a DMP can be a great way for companies to navigate a business world dominated by data.

Management 144

Management Advertising Data Lake Sales 144

AWS Big Data

OCTOBER 23, 2024

Amazon Managed Workflows for Apache Airflow (Amazon MWAA) is a fully managed service that builds upon Apache Airflow, offering its benefits while eliminating the need for you to set up, operate, and maintain the underlying infrastructure, reducing operational overhead while increasing security and resilience.

Interactive 115

Interactive Testing Data-driven Data Lake 115

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Metadata 84

Metadata Data Lake Dashboards Interactive 84

AWS Big Data

OCTOBER 25, 2023

Additionally, we show how to use AWS AI/ML services for analyzing unstructured data. Why it’s challenging to process and manage unstructured data Unstructured data makes up a large proportion of the data in the enterprise that can’t be stored in a traditional relational database management systems (RDBMS).

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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. availability. The examples are run on a Jupyter Notebook environment attached to the EMR cluster.

Data Lake 98

Data Lake Snapshot Metadata Optimization 98

David Menninger's Analyst Perspectives

OCTOBER 24, 2024

Data fabric refers to technology products that can be used to integrate, manage and govern data across distributed environments, supporting the cultural and organizational data ownership and access goals of data mesh.

Management 130

Management Data-driven Data Governance Data Lake 130

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

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

MARCH 4, 2024

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data.

Snapshot 132

Snapshot Data Lake Metadata Recreation/Entertainment 132

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