AWS Big Data Blog

Category: Amazon Redshift

Visualize database privileges on Amazon Redshift using Grafana

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data. As more users start querying data in a data warehouse, access control is paramount to protect valuable organizational […]

Simplify Online Analytical Processing (OLAP) queries in Amazon Redshift using new SQL constructs such as ROLLUP, CUBE, and GROUPING SETS

Amazon Redshift is a fully managed, petabyte-scale, massively parallel data warehouse that makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. We are continuously investing to make analytics easy with Redshift by simplifying SQL constructs and adding new operators. Now we are adding […]

Patterns for enterprise data sharing at scale

Data sharing is becoming an important element of an enterprise data strategy. AWS services like AWS Data Exchange provide an avenue for companies to share or monetize their value-added data with other companies. Some organizations would like to have a data sharing platform where they can establish a collaborative and strategic approach to exchange data […]

A hybrid approach in healthcare data warehousing with Amazon Redshift

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs. Loading complex multi-point datasets into a […]

Build a data storytelling application with Amazon Redshift Serverless and Toucan

This post was co-written with Django Bouchez, Solution Engineer at Toucan. Business intelligence (BI) with dashboards, reports, and analytics remains one of the most popular use cases for data and analytics. It provides business analysts and managers with a visualization of the business’s past and current state, helping leaders make strategic decisions that dictate the […]

Automate deployment of an Amazon QuickSight analysis connecting to an Amazon Redshift data warehouse with an AWS CloudFormation template

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. QuickSight provides easy integration with Amazon Redshift, providing […]

How OLX Group migrated to Amazon Redshift RA3 for simpler, faster, and more cost-effective analytics

This is a guest post by Miguel Chin, Data Engineering Manager at OLX Group and David Greenshtein, Specialist Solutions Architect for Analytics, AWS. OLX Group is one of the world’s fastest-growing networks of online marketplaces, operating in over 30 countries around the world. We help people buy and sell cars, find housing, get jobs, buy […]

Synchronize your Salesforce and Snowflake data to speed up your time to insight with Amazon AppFlow

This post was co-written with Amit Shah, Principal Consultant at Atos. Customers across industries seek meaningful insights from the data captured in their Customer Relationship Management (CRM) systems. To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service […]

­­Use fuzzy string matching to approximate duplicate records in Amazon Redshift

It’s common to ingest multiple data sources into Amazon Redshift to perform analytics. Often, each data source will have its own processes of creating and maintaining data, which can lead to data quality challenges within and across sources. One challenge you may face when performing analytics is the presence of imperfect duplicate records within the source data. This post presents one possible approach to addressing this challenge in an Amazon Redshift data warehouse using fuzzy matching.

Build a serverless analytics application with Amazon Redshift and Amazon API Gateway

Serverless applications are a modernized way to perform analytics among business departments and engineering teams. Business teams can gain meaningful insights by simplifying their reporting through web applications and distributing it to a broader audience. Use cases can include the following: Dashboarding – A webpage consisting of tables and charts where each component can offer […]