David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

The adoption of cloud environments for analytic workloads has been a key feature of the data platforms sector in recent years. For two-thirds (66%) of participants in ISG’s Data Lake Dynamic Insights Research, the primary data platform used for analytics is cloud based.

Data Warehouse 130

Data Warehouse Cost-Benefit Data Lake Software 130

AWS Big Data

OCTOBER 10, 2024

Amazon Redshift has established itself as a highly scalable, fully managed cloud data warehouse trusted by tens of thousands of customers for its superior price-performance and advanced data analytics capabilities. This allows you to maintain a comprehensive view of your data while optimizing for cost-efficiency.

Data Lake 120

Data Lake Data Warehouse Recreation/Entertainment Data-driven 120

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 115

Data Lake Statistics Broadcasting Optimization 115

AWS Big Data

AUGUST 21, 2024

The current scaling approach of Amazon Redshift Serverless increases your compute capacity based on the query queue time and scales down when the queuing reduces on the data warehouse. In this post, we describe how Redshift Serverless utilizes the new AI-driven scaling and optimization capabilities to address common use cases.

Optimization 108

Optimization Data Lake Data Warehouse Cost-Benefit 108

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

OCTOBER 30, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze your data using standard SQL and your existing business intelligence (BI) tools. Data ingestion is the process of getting data to Amazon Redshift.

Data Warehouse 110

Data Warehouse Sales Data Lake Recreation/Entertainment 110

AWS Big Data

NOVEMBER 7, 2024

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. times better price performance than other cloud data warehouses.

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

MAY 30, 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. Data store – The data store used a custom data model that had been highly optimized to meet low-latency query response requirements.

Data Warehouse 115

Data Warehouse Data Lake Cost-Benefit Structured Data 115

AWS Big Data

JUNE 10, 2024

Cloudinary is a cloud-based media management platform that provides a comprehensive set of tools and services for managing, optimizing, and delivering images, videos, and other media assets on websites and mobile applications.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

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 130

Data Lake Metadata Statistics Optimization 130

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

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

AWS Big Data

MARCH 2, 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. and later supports the Apache Iceberg framework for data lakes. AWS Glue 3.0 The following diagram illustrates the solution architecture.

Data Lake 137

Data Lake Data Processing Metadata Snapshot 137

AWS Big Data

JUNE 21, 2023

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 105

Data Warehouse Data Lake OLAP Cost-Benefit 105

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. Refer to Easy analytics and cost-optimization with Amazon Redshift Serverless to get started. For this post, we use Redshift Serverless. Choose Run all on each notebook tab.

Metadata 105

Metadata Sales Data Warehouse Optimization 105

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.

Data Warehouse 96

Data Warehouse Cost-Benefit Consulting Interactive 96

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

AWS Big Data

MAY 20, 2024

Whether you are new to Apache Iceberg on AWS or already running production workloads on AWS, this comprehensive technical guide offers detailed guidance on foundational concepts to advanced optimizations to build your transactional data lake with Apache Iceberg on AWS. He can be reached via LinkedIn.

Data Lake 129

Data Lake Big Data Cost-Benefit Data Warehouse 129

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. Maintaining data consistency and integrity across distributed data lakes is crucial for decision-making and analytics.

Data Lake 116

Data Lake Marketing Data Processing Management 116

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 114

Data Integration Data Lake Statistics Data-driven 114

Sisense

APRIL 9, 2021

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

DataKitchen

NOVEMBER 4, 2021

It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows. The DataKitchen Platform is a “ process hub” that masters and optimizes those processes. Cloud computing has made it much easier to integrate data sets, but that’s only the beginning.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Security Data Lake. Learn more about our Security Data Lake Solution. Workload discovery.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

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. You can add more such query optimization rules to the instructions.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

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. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 111

Data Lake Data Processing Metadata Snapshot 111

Sisense

DECEMBER 23, 2019

AI and ML are the only ways to derive value from massive data lakes, cloud-native data warehouses, and other huge stores of information. Your platform should be able to effortlessly connect to numerous large datasets: cloud-native data warehouses and data lakes with millions or billions of rows.

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. AWS Database Migration Service (AWS DMS) is used to securely transfer the relevant data to a central Amazon Redshift cluster. datazone_env_twinsimsilverdata"."cycle_end";')

IoT 111

IoT Machine Learning Metadata Data-driven 111

AWS Big Data

APRIL 24, 2025

SageMaker Lakehouse is a unified, open, and secure data lakehouse that now supports ABAC to provide unified access to general purpose Amazon S3 buckets, Amazon S3 Tables , Amazon Redshift data warehouses, and data sources such as Amazon DynamoDB or PostgreSQL. Set up a data lake admin. Choose Grant.

Sales 87

Sales Data Lake Management Data-driven 87

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 97

Data Lake Snapshot Optimization Data Transformation 97

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.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

O'Reilly on Data

OCTOBER 19, 2021

ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. With these five layers, we can present a highly productive, data-centric software interface that enables iterative development of large-scale data-intensive applications.

IT 364

IT Testing Experimentation Software 364

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. This property is set to true by default. availability.

Data Lake 98

Data Lake Snapshot Metadata Optimization 98

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

AWS Big Data

JUNE 23, 2023

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

Data Lake 95

Data Lake Dashboards Cost-Benefit Data Warehouse 95

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.

Data Warehouse 130

Data Warehouse Analytics Data Lake Machine Learning 130

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