AWS Big Data

OCTOBER 19, 2023

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure. Delta Lake doesn’t have a specific concept for incremental queries.

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Data Lake Data Warehouse Visualization Snapshot 122

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.

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Metadata Sales Data Warehouse Optimization 97

AWS Big Data

NOVEMBER 27, 2024

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis.

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AWS Big Data

NOVEMBER 26, 2024

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. For more examples and references to other posts, refer to the following GitHub repository.

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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. Big data and data warehousing.

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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.

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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.

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AWS Big Data

NOVEMBER 22, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that you can use to analyze your data at scale. With Data API session reuse, you can use a single long-lived session at the start of the ETL pipeline and use that persistent context across all ETL phases.

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AWS Big Data

OCTOBER 23, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that lets you analyze your data at scale. Amazon Redshift Serverless lets you access and analyze data without the usual configurations of a provisioned data warehouse. For more information, refer to Amazon Redshift clusters.

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Data Warehouse Metrics Broadcasting Dashboards 89

datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

AWS Big Data

DECEMBER 4, 2024

SageMaker brings together widely adopted AWS ML and analytics capabilities—virtually all of the components you need for data exploration, preparation, and integration; petabyte-scale big data processing; fast SQL analytics; model development and training; governance; and generative AI development.

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Data Analytics Analytics Data Lake Data Quality 86

CIO Business Intelligence

DECEMBER 11, 2024

To succeed in todays landscape, every company small, mid-sized or large must embrace a data-centric mindset. This article proposes a methodology for organizations to implement a modern data management function that can be tailored to meet their unique needs.

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Management Data Governance Data Science Reporting 111

AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. 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. Here, data modeling uses dbt on Amazon Redshift.

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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.

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AWS Big Data

FEBRUARY 20, 2024

The elasticity of Kinesis Data Streams enables you to scale the stream up or down, so you never lose data records before they expire. Analytical data storage The next service in this solution is Amazon Redshift, a fully managed, petabyte-scale data warehouse service in the cloud.

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Visualization Cost-Benefit Optimization B2B 114

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.

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Data Warehouse Management Snapshot Data Lake 92

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.

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Data Warehouse Data Lake OLAP Cost-Benefit 91

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. About the author Naidu Rongal i is a Big Data and ML engineer at Amazon.

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Metadata Data Lake Modeling Data Warehouse 89

AWS Big Data

AUGUST 22, 2024

In this post, we discuss how the Kaplan data engineering team implemented data integration from the Salesforce application to Amazon Redshift. Solution overview The high-level data flow starts with the source data stored in Amazon S3 and then integrated into Amazon Redshift using various AWS services.

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Data Warehouse Data Lake Data Integration Management 114

Smart Data Collective

OCTOBER 17, 2022

Big data is shaping our world in countless ways. Data powers everything we do. Exactly why, the systems have to ensure adequate, accurate and most importantly, consistent data flow between different systems. A point of data entry in a given pipeline. The destination is decided by the use case of the data pipeline.

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Data Warehouse Data Lake Visualization Big Data 145

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.

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AWS Big Data

MAY 20, 2024

It does so by bringing the familiarity of SQL tables to big data and capabilities such as ACID transactions, row-level operations (merge, update, delete), partition evolution, data versioning, incremental processing, and advanced query scanning. He can be reached via LinkedIn. He can be reached via LinkedIn.

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Data Lake Big Data Cost-Benefit Data Warehouse 109

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

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Data Warehouse Sales Visualization Data Processing 88

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.

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Visualization Sales Data Warehouse Management 82

AWS Big Data

MARCH 10, 2025

Although traditional scaling primarily responds to query queue times, the new AI-driven scaling and optimization feature offers a more sophisticated approach by considering multiple factors including query complexity and data volume. Our findings serve as a reference point rather than a universal benchmark.

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AWS Big Data

FEBRUARY 1, 2024

Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization. This will be your OLTP data store for transactional data. version cluster. version cluster.

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Data Warehouse Dashboards Risk Management Risk 132

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. OLTP databases are best at queries where we are doing point scans or short scans of the data, think “return the number of deposits by X user this week.”.

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Data Warehouse OLAP Statistics Cost-Benefit 78

AWS Big Data

NOVEMBER 17, 2023

For more information, refer SQL models. Seeds – These are CSV files in your dbt project (typically in your seeds directory), which dbt can load into your data warehouse using the dbt seed command. During the run, dbt creates a Directed Acyclic Graph (DAG) based on the internal reference between the dbt components.

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Snapshot Data Processing Testing Data Warehouse 104

Sisense

MARCH 20, 2019

To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-growing pile of Big Data that every company faces today. Data Warehousing.

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datapine

SEPTEMBER 29, 2022

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Why Do You Need Data Quality Management?

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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 108

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. Azure Data Explorer. Azure Data Lake Analytics. Data warehouses are designed for questions you already know you want to ask about your data, again and again.

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Data Lake Analytics Data Warehouse Machine Learning 116

Smart Data Collective

DECEMBER 13, 2022

However, computerization in the digital age creates massive volumes of data, which has resulted in the formation of several industries, all of which rely on data and its ever-increasing relevance. Data analytics and visualization help with many such use cases. It is the time of big data. Select a Storage Platform.

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Visualization Key Performance Indicator Sales Advertising 145

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.

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Data Integration Data Lake Statistics Data-driven 98

AWS Big Data

JUNE 2, 2023

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytic workloads. For more information, refer to Migrate Google BigQuery to Amazon Redshift using AWS Schema Conversion tool (SCT).

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Metadata Data Warehouse Big Data Analytics 121

AWS Big Data

NOVEMBER 17, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. Amazon Redshift now supports custom URLs or custom domain names for your data warehouse. Choose Create.

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Data Warehouse Management Software Strategy 117

AWS Big Data

JUNE 28, 2023

For more details, refer to the What’s New Post. There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. For this illustration, we use a provisioned Aurora database and an Amazon Redshift Serverless data warehouse.

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Data Warehouse Analytics Metrics Dashboards 96