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.

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Data Lake Data Warehouse Metadata Data Architecture 110

David Menninger's Analyst Perspectives

OCTOBER 31, 2024

I previously wrote about the importance of open table formats to the evolution of data lakes into data lakehouses. The concept of the data lake was initially proposed as a single environment where data could be combined from multiple sources to be stored and processed to enable analysis by multiple users for multiple purposes.

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Data Lake Unstructured Data Data Warehouse Software 130

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. Test access using SageMaker Studio in the consumer account.

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Data Lake Metadata Data Warehouse Data Processing 99

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.

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Data Lake Data Processing Metadata Snapshot 130

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.

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Data Lake Sales Data Warehouse Snapshot 118

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.

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Data Lake Metadata Statistics Optimization 127

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. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

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Data Lake Data Processing Metadata Snapshot 106

Data Virtualization

OCTOBER 18, 2022

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

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Data Warehouse ROI Data Integration Internet of Things 98

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

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Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

OCTOBER 25, 2024

Amazon Redshift is 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. The new technique captures real-time statistical metadata gathered during data ingestion without incurring additional computational overhead.

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Statistics Data Warehouse Metadata Data Lake 91

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. show() The snapshots that have expired show the latest snapshot ID as null.

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Data Lake Snapshot Metadata Optimization 93

AWS Big Data

APRIL 6, 2023

In this post, Morningstar’s Data Lake Team Leads discuss how they utilized tag-based access control in their data lake with AWS Lake Formation and enabled similar controls in Amazon Redshift. We realized we needed a data warehouse to cater to all of these consumer requirements, so we evaluated Amazon Redshift.

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Data Warehouse Data Lake Management Data-driven 94

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. It works in Salesforce just like any other native Salesforce data,” Carlson said.

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Data Integration Data Lake Data Warehouse Metadata 117

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Tags allows you to assign metadata to your AWS resources. Analytics Specialist based out of Northern Virginia, specialized in the design and implementation of analytics and data lake solutions.

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Data Warehouse Management Snapshot Data Lake 94

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation.

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Data Lake Data Warehouse Marketing Management 95

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.

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Data Lake Metadata Testing Data Warehouse 93

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. It allows us to independently upgrade the Virtual Warehouses and Database Catalogs.

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Data Warehouse Snapshot Metadata Cost-Benefit 80

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

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Data Warehouse Cost-Benefit Consulting Interactive 95

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

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Data Lake Dashboards Cost-Benefit Data Warehouse 52

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

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Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

NOVEMBER 14, 2024

You can learn how to query Delta Lake native tables through UniForm from different data warehouses or engines such as Amazon Redshift as an example of expanding data access to more engines. How Delta Lake UniForm works UniForm allows other table format clients such as Apache Iceberg to access Delta Lake tables.

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Metadata Data Warehouse Big Data Data Lake 109

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. The following diagram illustrates this use case’s historical data migration architecture.

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Data Quality Data Lake Data Warehouse Metrics 99

Cloudera

OCTOBER 10, 2024

It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse. Table Cleanup: As tables grow, they often accumulate unused data files, manifest files, and snapshots that aren’t needed anymore.

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Optimization Snapshot Data Lake Cost-Benefit 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.

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Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Data Warehouse Data Lake Analytics Machine Learning 116

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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Data Lake Data Warehouse Machine Learning Cost-Benefit 95

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.

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Metadata Data Lake Data Warehouse Data Quality 52

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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Data Lake Data Warehouse Machine Learning Cost-Benefit 93

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

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Data Lake Unstructured Data Data Warehouse Data Quality 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.

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Metadata Sales Data Warehouse Optimization 98

AWS Big Data

FEBRUARY 29, 2024

First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

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Data Governance Unstructured Data Metadata Data Lake 113

IBM Big Data Hub

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. New insights and relationships are found in this combination. All of this supports the use of AI.

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Data Lake Metadata Data Warehouse Cost-Benefit 77

Cloudera

NOVEMBER 5, 2020

Many organizations struggle to meet growing and variable data warehouse demands. This is exactly what Cloudera Data Platform (CDP) provides to the Cloudera Data Warehouse. CDP is a data platform that is optimized for both business units and central IT. . Main Security Features.

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Data Lake Data Warehouse Metadata Optimization 74

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.

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Data Lake Cost-Benefit Data-driven Data Warehouse 115

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt.

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Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance.

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Data Lake Snapshot Metadata Optimization 109

Cloudera

NOVEMBER 15, 2024

A Better Way Forward: Cloudera’s Open Data Lakehouse Cloudera offers a solution to these challenges with its open data lakehouse, which combines the flexibility and scalability of data lake storage with data warehouse functionality to unify and simplify the management of cyber log data.

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Analytics Metadata Snapshot Data-driven 76