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 111

Data Warehouse Sales Data Lake Recreation/Entertainment 111

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

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? What role do technology and IT infrastructure play? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

CIO Business Intelligence

DECEMBER 20, 2024

Uniteds embrace of SageMaker and Bedrock as well as Amazon Q is going to be a game changer for building data products, said Mai-LanTomsenBukovec, AWS vice president of technology, who pointed to United Data Hub as a transformational component in its AI journey at re:Invent.

IT 131

IT Unstructured Data Experimentation Data Lake 131

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. Solution overview Amazon Redshift is an industry-leading cloud data warehouse.

Data Warehouse 115

Data Warehouse Data Lake Cost-Benefit Structured Data 115

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

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster. Option 3: Azure Data Lakes.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

AWS Big Data

FEBRUARY 26, 2025

Given the diverse data integration needs of customers, AWS offers a robust data integration system through multiple services including Amazon EMR , Amazon Athena , Amazon Managed Workflows for Apache Airflow (Amazon MWAA) , Amazon Managed Streaming for Apache Kafka (MSK) , Amazon Kinesis , and others.

Data Integration 103

Data Integration Data Lake Data Warehouse Unstructured Data 103

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 121

Data Architecture Management Consulting Internet of Things 121

AWS Big Data

JUNE 10, 2024

One of the key challenges in modern big data management is facilitating efficient data sharing and access control across multiple EMR clusters. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. Test access using SageMaker Studio in the consumer account.

Data Lake 117

Data Lake Metadata Data Warehouse Data Processing 117

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

JUNE 10, 2024

This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used. The landscape of data technology is swiftly advancing, driven frequently by projects led by the open source community in general and the Apache foundation specifically.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a unified view of all data. Its code generation architecture uses a visual interface to create Java or SQL code.

Management 324

Management Data Warehouse Data Quality Data Integration 324

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

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

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

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

CIO Business Intelligence

AUGUST 18, 2022

To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We For Guadagno, the need to match vaccine availability with patient demand came at the right moment, technologically speaking. Lakehouses redeem the failures of some data lakes. That’s how we got here.

Data Lake 139

Data Lake Data Warehouse Unstructured Data Business Intelligence 139

DataKitchen

NOVEMBER 4, 2021

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

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.

Data Warehouse 98

Data Warehouse Data Lake Management Data-driven 98

Sisense

DECEMBER 23, 2019

Artificial Intelligence and machine learning are the future of every industry, especially data and analytics. In Growing Up with AI , we help you keep up with all the ways this pioneering technology is changing the world. Use AI to tackle huge datasets. Let’s talk about AI and machine learning (ML).

Data Lake 86

Data Lake Machine Learning Data Warehouse Digital Transformation 86

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.

Data Lake 98

Data Lake Data Warehouse Marketing Management 98

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 96

Data Lake Dashboards Cost-Benefit Data Warehouse 96

AWS Big Data

JANUARY 15, 2025

With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially. However, much of this data remains siloed and making it accessible for different purposes and other departments remains complex. datazone_env_twinsimsilverdata"."cycle_end";')

IoT 111

IoT Machine Learning Metadata Data-driven 111

AWS Big Data

OCTOBER 17, 2023

With Amazon Redshift, you can use standard SQL to query data across your data warehouse, operational data stores, and data lake. Migrating a data warehouse can be complex. You have to migrate terabytes or petabytes of data from your legacy system while not disrupting your production workload.

Data Warehouse 111

Data Warehouse Data Processing Data Lake Management 111

CIO Business Intelligence

NOVEMBER 25, 2022

Carhartt’s signature workwear is near ubiquitous, and its continuing presence on factory floors and at skate parks alike is fueled in part thanks to an ongoing digital transformation that is advancing the 133-year-old Midwest company’s operations to make the most of advanced digital technologies, including the cloud, data analytics, and AI.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

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. Can it also help write SQL queries? The answer is yes.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

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

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 102

Data Lake Testing Snapshot Sales 102

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.

Data Lake 118

Data Lake Unstructured Data Data Warehouse Big Data 118

AWS Big Data

NOVEMBER 14, 2024

This post explores how to start using Delta Lake UniForm on Amazon Web Services (AWS). 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.

Metadata 122

Metadata Data Warehouse Big Data Data Lake 122

AWS Big Data

DECEMBER 20, 2024

You can now generate data integration jobs for various data sources and destinations, including Amazon Simple Storage Service (Amazon S3) data lakes with popular file formats like CSV, JSON, and Parquet, as well as modern table formats such as Apache Hudi , Delta , and Apache Iceberg.

Data Integration 105

Data Integration Visualization Data Processing Data Lake 105

AWS Big Data

DECEMBER 12, 2024

Complex queries, on the other hand, refer to large-scale data processing and in-depth analysis based on petabyte-level data warehouses in massive data scenarios. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. Here, data modeling uses dbt on Amazon Redshift.

Snapshot 97

Snapshot Recreation/Entertainment Experimentation Data Lake 97

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

O'Reilly on Data

OCTOBER 19, 2021

What does a modern technology stack for streamlined ML processes look like? Why: Data Makes It Different. ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. Can’t we just fold it into existing DevOps best practices?

IT 364

IT Testing Experimentation Software 364