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 100

Data Lake Data Warehouse Metadata Data Architecture 100

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 97

Data Lake Data Processing Metadata Snapshot 97

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 120

Data Lake Data Processing Metadata Snapshot 120

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. An entity can act both as a producer of data assets and as a consumer of data assets.

Data Lake 90

Data Lake Metadata Data Warehouse Data Processing 90

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 119

Data Lake Metadata Statistics Optimization 119

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 85

Data Lake Snapshot Metadata Optimization 85

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 84

Data Lake Metadata Testing Data Warehouse 84

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

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

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 92

Data Lake Metadata Cost-Benefit Management 92

AWS Big Data

FEBRUARY 6, 2023

For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to discover and catalog data in the background. This allows users to search and find relevant data from multiple data sources. For instructions, refer to How to Set Up a MongoDB Cluster.

Metadata 75

Metadata Data Lake Machine Learning Big Data 75

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 117

Snapshot Data Lake Metadata Recreation/Entertainment 117

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 87

Data Lake Data Warehouse Marketing Management 87

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. Without business context, business users are less likely to use the data lake and insights will be hard to come by.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

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. Appendix 1.

Metadata 98

Metadata Data Warehouse Big Data Data Lake 98

Alation

FEBRUARY 20, 2020

When it was no longer a hard requirement that a physical data model be created upon the ingestion of data, there was a resulting drop in richness of the description and consistency of the data stored in Hadoop. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

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 107

Snapshot Data Lake Metadata Optimization 107

David Menninger's Analyst Perspectives

OCTOBER 24, 2024

Although the terms data fabric and data mesh are often used interchangeably, I previously explained that they are distinct but complementary. With Denodo Platform 9, the company also added enhanced federated governance support to enable the creation, management and reuse of data products by different business units and teams.

Management 130

Management Data-driven Data Governance Data Lake 130

AWS Big Data

MAY 9, 2024

Additionally, you can use the power of SQL in a view to express complex boundaries in data across multiple tables that can’t be expressed with simpler permissions. Data lakes provide customers the flexibility required to derive useful insights from data across many sources and many use cases.

Data Lake 90

Data Lake Metadata Management Big Data 90

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

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 117

Optimization Snapshot Data Lake Metadata 117

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

Data Integration 103

Data Integration Data Lake Data Warehouse Metadata 103

AWS Big Data

SEPTEMBER 12, 2024

Along with the Glue Data Catalog’s automated compaction feature, these storage optimizations can help you reduce metadata overhead, control storage costs, and improve query performance. Iceberg creates a new version called a snapshot for every change to the data in the table.

Optimization 108

Optimization Snapshot Metadata Metrics 108

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 118

Data Lake Analytics Dashboards Metrics 118

AWS Big Data

SEPTEMBER 12, 2024

The new table needs to be refreshed periodically to get the latest data from the shared Data Cloud objects with this solution. Considerations when using data sharing in Amazon Redshift For a comprehensive list of considerations and limitations of data sharing, refer to Considerations when using data sharing in Amazon Redshift.

Data Lake 92

Data Lake Analytics Data-driven Data Strategy 92

AWS Big Data

FEBRUARY 29, 2024

To provide a response that includes the enterprise context, each user prompt needs to be augmented with a combination of insights from structured data from the data warehouse and unstructured data from the enterprise data lake. It also monitors bias drift in your model’s predictions and feature attribution.

Data Governance 102

Data Governance Unstructured Data Metadata Data Lake 102

AWS Big Data

NOVEMBER 14, 2024

Amazon Data Firehose – Data Firehose is an extract, transform, and load (ETL) service that reliably captures, transforms, and delivers streaming data to data lakes, data stores, and analytics services. AWS Glue – The AWS Glue Data Catalog is your persistent technical metadata store in the AWS Cloud.

Data Lake 86

Data Lake Metadata Testing Data-driven 86

AWS Big Data

AUGUST 3, 2023

Today’s modern data lakes span multiple accounts, AWS Regions, and lines of business in organizations. It’s important that their data solution gives them the ability to share and access data securely and safely across Regions. A resource link is a Data Catalog object that is a link to a database or table.

Data Lake 86

Data Lake Metadata Management Data Processing 86

AWS Big Data

AUGUST 16, 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. Iceberg captures metadata information on the state of datasets as they evolve and change over time. For more details, refer to Creating Apache Iceberg tables.

Data Lake 79

Data Lake Metadata Snapshot Management 79

AWS Big Data

OCTOBER 9, 2024

Today, customers are embarking on data modernization programs by migrating on-premises data warehouses and data lakes to the AWS Cloud to take advantage of the scale and advanced analytical capabilities of the cloud. Compare ongoing data that is replicated from the source on-premises database to the target S3 data lake.

Data Quality 89

Data Quality Data Lake Data Warehouse Metrics 89

Ontotext

APRIL 10, 2024

In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata. Teams can’t access data to build their business use cases. For example, a product data tag is basic metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

AUGUST 5, 2024

These business units have varying landscapes, where a data lake is managed by Amazon Simple Storage Service (Amazon S3) and analytics workloads are run on Amazon Redshift , a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.

Data Lake 83

Data Lake Finance Sales Management 83

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

NOVEMBER 7, 2024

Amazon Q generative SQL for Amazon Redshift uses generative AI to analyze user intent, query patterns, and schema metadata to identify common SQL query patterns directly within Amazon Redshift, accelerating the query authoring process for users and reducing the time required to derive actionable data insights.

Metadata 89

Metadata Sales Data Warehouse Optimization 89

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 105

Data Lake Cost-Benefit Data-driven Data Warehouse 105

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 80

Metadata Data Lake Data Processing Data-driven 80

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67