Remove 2000 Remove Data Warehouse Remove Technology
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How to Build a Performant Data Warehouse in Redshift

Sisense

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. Through this transition, there have been new technologies that change the way data should be stored, and Redshift is no different. OLTP vs OLAP.

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Q&A with Greg Rahn – The changing Data Warehouse market

Cloudera

I would like to start off by asking you to tell us about your background and what kicked off your 20-year career in relational database technology? And then I moved from Madison, Wisconsin to San Francisco in 2000, to chase the dotcom dream. Let’s talk about big data and Apache Impala. Michael Moreno: Nice!

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Integrate Okta with Amazon Redshift Query Editor V2 using AWS IAM Identity Center for seamless Single Sign-On

AWS Big Data

This integration simplifies the authentication and authorization process for Amazon Redshift users using Query Editor V2 or Amazon Quicksight , making it easier for them to securely access your data warehouse. Note: Your organization’s IdC instance must be in the same region as the Amazon Redshift data warehouse you’re connecting to.

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Wonderla Holidays goes digital to enhance business and customer fun

CIO Business Intelligence

The company, listed on both the National Stock Exchange and the Bombay Stock Exchange, operates three amusement parks in Kochi, Bengaluru, and Hyderabad that were set up in 2000, 2005, and 2016, respectively, and plans to open two more amusement parks in the near future, in Chennai and Bhubaneswar. One pulse sends 150 bytes of data.

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Self-Service BI vs Traditional BI: What’s Next?

Alation

This led to the birth of separate systems for reporting: the enterprise data warehouse. For the first time, the focus of a system became business questions, where data was denormalized. A shift emerged around 2000 with the initial discussions regarding digital transformation. The request model started to fray.

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Single sign-on with Amazon Redshift Serverless with Okta using Amazon Redshift Query Editor v2 and third-party SQL clients

AWS Big Data

Amazon Redshift Serverless makes it easy to run and scale analytics in seconds without the need to set up and manage data warehouse clusters. Customers use their preferred SQL clients to analyze their data in Redshift Serverless. An Redshift Serverless data warehouse. If you don’t have one, you can sign up for one.

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Build a real-time GDPR-aligned Apache Iceberg data lake

AWS Big Data

Create the AWS Glue Data Catalog database The AWS Glue Data Catalog contains references to data that is used as sources and targets of your extract, transform, and load (ETL) jobs in AWS Glue. To create your data warehouse or data lake, you must catalog this data.