O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. However, the concept is quite abstract.

IT 364

IT Testing Experimentation Software 364

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. For more details on tagging, refer to Tagging resources overview. For more tagging best practices, refer to Tagging AWS resources. Choose Save changes. About the Authors Sandeep Bajwa is a Sr.

Data Warehouse 98

Data Warehouse Management Snapshot Data Lake 98

CIO Business Intelligence

DECEMBER 11, 2024

It was not alive because the business knowledge required to turn data into value was confined to individuals minds, Excel sheets or lost in analog signals. We are now deciphering rules from patterns in data, embedding business knowledge into ML models, and soon, AI agents will leverage this data to make decisions on behalf of companies.

Management 111

Management Data Governance Data Science Reporting 111

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Cloud based solutions are the future of the data warehousing market.

Technology 144

Technology Data Warehouse Big Data Machine Learning 144

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

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. For instructions, refer to Data analyst permissions.

Sales 87

Sales Data Lake Management Data-driven 87

AWS Big Data

FEBRUARY 20, 2024

In this post, we discuss how to architect a near-real-time analytics solution with AWS managed analytics, AI and machine learning (ML), and database services. Solution overview The most common workloads, agnostic of industry, involve transactional data.

Visualization 124

Visualization Cost-Benefit Optimization B2B 124

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.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

Smart Data Collective

JUNE 6, 2021

Before diving into whether or not Google BigQuery is the future of big data analytics, it’s vital to firstly understand what “big data analytics” actually means. Big data analytics advantages. Is Google BigQuery the future of big data analytics? References. What is Big Data?” What is Google BigQuery?

Big Data 137

Big Data Data Analytics Analytics Cost-Benefit 137

datapine

SEPTEMBER 27, 2022

Recently published in 2021, “SQL for Data Scientists” by author and experienced data scientist, Rénee Teate, teaches its readers all the skills that data scientists use the most in their daily work. Here is an excerpt from one: “I use SQL daily, and this was a great reference towards using advanced SQL to get analytics insights.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Learn more about the AWS zero-ETL future with newly launched AWS databases integrations with Amazon Redshift.

Data Warehouse 111

Data Warehouse Machine Learning Data-driven Data Lake 111

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

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

AWS Big Data

MARCH 6, 2025

Tens of thousands of customers use Amazon Redshift for modern data analytics at scale, delivering up to three times better price-performance and seven times better throughput than other cloud data warehouses. Refer to IAM Identity Center identity source tutorials for the IdP setup. IAM Identity Center enabled.

Visualization 102

Visualization Sales Data Warehouse Management 102

DataKitchen

NOVEMBER 20, 2021

We often refer to data operations and analytics as a factory. We distinguish between owning the assembly lines of the data factory (DataOps Engineer) and owning individual steps within the assembly lines (data scientists, engineers, etc.). . Consider a machine learning example.

Testing 246

Testing Machine Learning Data Warehouse Analytics 246

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview. Azure Data Factory. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Smart Data Collective

OCTOBER 17, 2022

A point of data entry in a given pipeline. Examples of an origin include storage systems like data lakes, data warehouses and data sources that include IoT devices, transaction processing applications, APIs or social media. The final point to which the data has to be eventually transferred is a destination.

Data Warehouse 145

Data Warehouse Data Lake Visualization Big Data 145

AWS Big Data

APRIL 10, 2024

“Data is at the center of every application, process, and business decision. Customers across industries are becoming more data driven and looking to increase revenue, reduce cost, and optimize their business operations by implementing near real time analytics on transactional data, thereby enhancing agility.

Data Warehouse 119

Data Warehouse Analytics Metrics Snapshot 119

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. Versioning serves two main purposes: You can refer to prior versions of a model for troubleshooting or audit purposes.

Modeling 116

Modeling Data Warehouse Machine Learning Recreation/Entertainment 116

Smart Data Collective

DECEMBER 13, 2022

Five Best Practices for Data Analytics. Extracted data must be saved someplace. There are several choices to consider, each with its own set of advantages and disadvantages: Data warehouses are used to store data that has been processed for a specific function from one or more sources. Select a Storage Platform.

Visualization 145

Visualization Key Performance Indicator Sales Advertising 145

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 113

Data Lake Data Warehouse Data-driven Optimization 113

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

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. If you’re new to Amazon DataZone, refer to Getting started.

Data Lake 118

Data Lake Data Warehouse Unstructured Data Data Governance 118

Sisense

APRIL 17, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. Why use a materialized view?

Data Warehouse 90

Data Warehouse Visualization Statistics Machine Learning 90

AWS Big Data

AUGUST 7, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Solution overview Amazon Forecast is a fully managed time series forecasting service based on machine learning.

Forecasting 98

Forecasting Data Warehouse Machine Learning Modeling 98

AWS Big Data

JANUARY 30, 2025

Diagram 1: Overall architecture of the solution, using AWS Step Functions, Amazon Redshift and Amazon S3 The following AWS services were used to shape our new ETL architecture: Amazon Redshift A fully managed, petabyte-scale data warehouse service in the cloud.

Data Warehouse 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

AWS Big Data

MARCH 18, 2024

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.

Data Warehouse 113

Data Warehouse Visualization Snapshot Data-driven 113

AWS Big Data

MAY 16, 2024

Traditionally, spatial data is represented through a geography or geometry in which features are geolocated on the earth by a long reference string describing the coordinates of every vertex. Indexed data can be quickly joined across different datasets and aggregated at different levels of precision. But what makes them special?

Data Warehouse 119

Data Warehouse Visualization Cost-Benefit Data-driven 119

AWS Big Data

JUNE 25, 2024

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. This external DLO acts as a storage container, housing metadata for your federated Redshift data.

Data Lake 122

Data Lake Cost-Benefit Data-driven Data Warehouse 122

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

CIO Business Intelligence

OCTOBER 19, 2023

You can also use Power BI to prepare and manage high-quality data to use across the business in other tools, from low-code apps to machine learning. What-if parameters also create calculated measures you can reference elsewhere.

Slice and Dice 126

Slice and Dice Scorecard Metrics Visualization 126

AWS Big Data

NOVEMBER 10, 2023

Amazon Redshift offers seamless integration with Apache Spark, allowing you to easily access your Redshift data on both Amazon Redshift provisioned clusters and Amazon Redshift Serverless. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime.

Data Processing 111

Data Processing Data Lake Data Warehouse Optimization 111

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 111

Enterprise Data Warehouse Data Lake Optimization 111

AWS Big Data

MARCH 21, 2024

The extract, transform, and load (ETL) process has been a common pattern for moving data from an operational database to an analytics data warehouse. ELT is where the extracted data is loaded as is into the target first and then transformed. Refer to Zero-ETL integration costs (Preview) for further details.

Data Warehouse 111

Data Warehouse Metrics Statistics Optimization 111

CIO Business Intelligence

JULY 30, 2024

Many of the AI use cases entrenched in business today use older, more established forms of AI, such as machine learning, or don’t take advantage of the “generative” capabilities of AI to generate text, pictures, and other data. Many AI experts say the current use cases for generative AI are just the tip of the iceberg.

Insurance 144

Insurance Machine Learning Interactive Finance 144

AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

Data Warehouse 98

Data Warehouse Analytics Metadata Dashboards 98