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Databricks’ new data lakehouse aims at media, entertainment sector

CIO Business Intelligence

After launching industry-specific data lakehouses for the retail, financial services and healthcare sectors over the past three months, Databricks is releasing a solution targeting the media and the entertainment (M&E) sector. Features focus on media and entertainment firms.

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Data Warehouse Migration: How to Make This Strategic Move

Octopai

Migrating a data fulfillment center (i.e. warehouse). Your data warehouse is not too different from an Amazon fulfillment center. No one wants to disrupt this level of complexity in order to recreate it elsewhere. Your old data warehouse has become deprecated. Ready to take on the job?

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Complexity Drives Costs: A Look Inside BYOD and Azure Data Lakes

Jet Global

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.

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How EchoStar ingests terabytes of data daily across its 5G Open RAN network in near real-time using Amazon Redshift Serverless Streaming Ingestion

AWS Big Data

EchoStar , a connectivity company providing television entertainment, wireless communications, and award-winning technology to residential and business customers throughout the US, deployed the first standalone, cloud-native Open RAN 5G network on AWS public cloud.

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Implement disaster recovery with Amazon Redshift

AWS Big Data

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can start with just a few hundred gigabytes of data and scale to a petabyte or more. This enables you to use your data to acquire new insights for your business and customers. Document the entire disaster recovery process.

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Using DataOps to Drive Agility and Business Value

DataKitchen

Previously we would have a very laborious data warehouse or data mart initiative and it may take a very long time and have a large price tag. Before we jump into a methodology or even a data strategy-based approach, what are we trying to accomplish? Tyo pointed out, “Don’t do data for data’s sake.

Metrics 211
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How FanDuel adopted a modern Amazon Redshift architecture to serve critical business workloads

AWS Big Data

In this post, we share how FanDuel moved from a DC2 nodes architecture to a modern Amazon Redshift architecture, which includes Redshift provisioned clusters using RA3 instances , Amazon Redshift data sharing , and Amazon Redshift Serverless. Their individual, product-specific, and often on-premises data warehouses soon became obsolete.