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 116

Data Lake Sales Data Warehouse Snapshot 116

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

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 104

Data Lake Data Processing Metadata Snapshot 104

AWS Big Data

JUNE 10, 2024

Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. To address this challenge, organizations can deploy a data mesh using AWS Lake Formation that connects the multiple EMR clusters. The data resides on Amazon S3, which reduces the storage costs significantly.

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Data Lake Metadata Data Warehouse Data Processing 96

AWS Big Data

DECEMBER 4, 2024

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. This strategy supports each division’s autonomy to implement their own data catalogs and decide which data products to publish to the group-level catalog.

Metadata 94

Metadata Data Governance Data Quality Data-driven 94

AWS Big Data

DECEMBER 4, 2024

Amazon SageMaker Lakehouse , now generally available, unifies all your data across Amazon Simple Storage Service (Amazon S3) data lakes and Amazon Redshift data warehouses, helping you build powerful analytics and AI/ML applications on a single copy of data. Having confidence in your data is key.

Data Analytics 86

Data Analytics Analytics Data Lake Data Quality 86

AWS Big Data

OCTOBER 21, 2024

However, enterprises often encounter challenges with data silos, insufficient access controls, poor governance, and quality issues. Embracing data as a product is the key to address these challenges and foster a data-driven culture. Amazon Athena is used to query, and explore the data.

Sales 105

Sales Data-driven Data Processing Key Performance Indicator 105

CIO Business Intelligence

APRIL 8, 2025

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

DataKitchen

AUGUST 9, 2021

The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution. The domain requires a team that creates/updates/runs the domain, and we can’t forget metadata: catalogs, lineage, test results, processing history, etc., …. Figure 5: Domain interfaces as URLs.

Testing 246

Testing Data Lake Metadata Publishing 246

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 59

Analytics Data Lake Metadata Data Warehouse 59

AWS Big Data

MARCH 5, 2025

Solution overview This solution provides a streamlined way to enable cross-account data collaboration using Amazon DataZone domain association while maintaining security and governance. Data publishers : Users in producer AWS accounts. Data subscribers : Users in consumer AWS accounts.

Analytics 59

Analytics Publishing Metadata Sales 59

AWS Big Data

JULY 25, 2024

Solution To address the challenge, ATPCO sought inspiration from a modern data mesh architecture. In Amazon DataZone, data owners can publish their data and its business catalog (metadata) to ATPCO’s DataZone domain. Data consumers can then search for relevant data assets using these human-friendly metadata terms.

Data Lake 106

Data Lake Metadata Sales Publishing 106

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. In 2022 , we talked about the enhancements we had done to these services. Bien intégré!

Data Lake 105

Data Lake Metadata Data Governance Statistics 105

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 114

Metadata Data Lake Publishing Data Governance 114

AWS Big Data

JUNE 19, 2023

Security Lake automatically centralizes security data from cloud, on-premises, and custom sources into a purpose-built data lake stored in your account. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

Publishing 96

Publishing Dashboards Visualization Management 96

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. The target accounts read data from the source account S3 buckets.

Metadata 59

Metadata Data Lake Machine Learning Big Data 59

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 87

Metadata Data Lake Data Processing Data-driven 87

DataKitchen

OCTOBER 11, 2021

Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments. The automated orchestration published the data to an AWS S3 Data Lake. Monitoring Job Metadata.

Testing 152

Testing Metadata Dashboards Statistics 152

AWS Big Data

DECEMBER 16, 2024

This approach simplifies your data journey and helps you meet your security requirements. The SageMaker Lakehouse data connection testing capability boosts your confidence in established connections. About the Authors Chiho Sugimoto is a Cloud Support Engineer on the AWS Big Data Support team. Choose Run all.

Visualization 72

Visualization Data Processing Testing Publishing 72

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 101

Data Lake Cost-Benefit Metadata Big Data 101

In(tegrate) the Clouds

MAY 1, 2016

SnapLogic published Eight Data Management Requirements for the Enterprise Data Lake. They are: Storage and Data Formats. Metadata and Governance. The company also recently hosted a webinar on Democratizing the Data Lake with Constellation Research and published 2 whitepapers from Mark Madsen.

Data Lake 40

Data Lake Enterprise Management Metadata 40

AWS Big Data

JULY 8, 2024

Introduction to OpenLineage compatible data lineage The need to capture data lineage consistently across various analytical services and combine them into a unified object model is key in uncovering insights from the lineage artifact. To learn more, refer to Creating inventory and published data in Amazon DataZone.

Visualization 109

Visualization Metadata Publishing Sales 109

AWS Big Data

MAY 1, 2024

Solution overview OneData defines three personas: Publisher – This role includes the organizational and management team of systems that serve as data sources. Responsibilities include: Load raw data from the data source system at the appropriate frequency. It is crucial in data governance and data management.

Dashboards 122

Dashboards Publishing Data-driven Cost-Benefit 122

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

AWS Big Data

DECEMBER 19, 2024

The business end-users were given a tool to discover data assets produced within the mesh and seamlessly self-serve on their data sharing needs. The integration of Databricks Delta tables into Amazon DataZone is done using the AWS Glue Data Catalog. The following figure illustrates the data mesh architecture.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

AWS Big Data

JULY 29, 2024

Amazon DataZone is a powerful data management service that empowers data engineers, data scientists, product managers, analysts, and business users to seamlessly catalog, discover, analyze, and govern data across organizational boundaries, AWS accounts, data lakes, and data warehouses.

Data Warehouse 91

Data Warehouse Sales Metadata Publishing 91

AWS Big Data

AUGUST 5, 2024

For example, a marketing analysis data product can bundle various data assets such as marketing campaign data, pipeline data, and customer data. With the grouping capabilities of data products, data producers can manage and control access to the underlying data assets with just a few steps.

Metadata 59

Metadata Sales Data Lake Publishing 59

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Starting with Amazon EMR release 6.7.0,

Data Lake 90

Data Lake Data Governance Data Architecture Machine Learning 90

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. Let’s say that this company is located in Europe and the data product must comply with the GDPR.

Data Lake 117

Data Lake Management Metrics Data Warehouse 117

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 105

Management Advertising Data Lake Sales 105

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale.

Management 79

Management Metadata Data Architecture Data Lake 79

AWS Big Data

JUNE 26, 2024

New feature: Custom AWS service blueprints Previously, Amazon DataZone provided default blueprints that created AWS resources required for data lake, data warehouse, and machine learning use cases. You can build projects and subscribe to both unstructured and structured data assets within the Amazon DataZone portal.

Data Lake 103

Data Lake Data Warehouse Unstructured Data Data Governance 103

Cloudera

JANUARY 19, 2022

Cloudera Data Platform (CDP) scored among the top 10 vendors on all four Analytical Use Cases — Data Warehouse, Logical Data Warehouse, Data Lake and Operational Intelligence in the Critical Capabilities for Cloud Database Management Systems for Analytics Use Cases. and/or its affiliates in the U.S.

Reporting 90

Reporting Data Warehouse Data Lake Machine Learning 90

Cloudera

SEPTEMBER 9, 2022

This is the promise of the modern data lakehouse architecture. analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.”

Metadata 102

Metadata Machine Learning Unstructured Data Data Lake 102

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 79

Analytics Data Warehouse Data Lake Metadata 79

AWS Big Data

MARCH 29, 2024

Data Firehose uses an AWS Lambda function to transform data and ingest the transformed records into an Amazon Simple Storage Service (Amazon S3) bucket. An AWS Glue crawler scans data on the S3 bucket and populates table metadata on the AWS Glue Data Catalog. Choose Publish dashboard.

Metrics 119

Metrics Visualization Dashboards Publishing 119