Remove Data Warehouse Remove Modeling Remove Recreation/Entertainment
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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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Accelerate your data workflows with Amazon Redshift Data API persistent sessions

AWS Big Data

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that you can use to analyze your data at scale. This persistent session model provides the following key benefits: The ability to create temporary tables that can be referenced across the entire session lifespan.

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Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

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. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. Here, data modeling uses dbt on Amazon Redshift.

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How to Future-Proof Your Business Systems with a Data Warehouse

Jet Global

Interestingly, you can address many of them very effectively with a data warehouse. It’s a much more complicated matter to recreate the history, showing which payments were applied to which invoices in which amounts. The Data Warehouse Solution. Pre-Staging Migration Data in the Data Warehouse.

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Implement model versioning with Amazon Redshift ML

AWS Big Data

Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. In previous posts, we demonstrated how you can use the automatic model training capability of Redshift ML to train classification and regression models.

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Peloton embraces Amazon Redshift to unlock the power of data during changing times

AWS Big Data

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

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Of Muffins and Machine Learning Models

Cloudera

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. Will the model correctly determine it is a muffin or get confused and think it is a chihuahua? The extent to which we can predict how the model will classify an image given a change input (e.g. Model Visibility.