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How HR&A uses Amazon Redshift spatial analytics on Amazon Redshift Serverless to measure digital equity in states across the US

AWS Big Data

HR&A has used Amazon Redshift Serverless and CARTO to process survey findings more efficiently and create custom interactive dashboards to facilitate understanding of the results. The following are sample screenshots of the dashboards that show survey responses by zip code.

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What is a Data Pipeline?

Jet Global

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

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Connect your data for faster decisions with AWS

AWS Big Data

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. They used Amazon Aurora MySQL zero-ETL integration with Amazon Redshift to achieve this.

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Accelerate Your Data Mesh in the Cloud with Cloudera Data Engineering and Modak NabuTM

Cloudera

Modak Nabu reliably curates datasets for any line of business and personas, from business analysts to data scientists. Customers using Modak Nabu with CDP today have deployed Data Lakes and. An executive dashboard shows the status of crawlers, pipelines, and data profiling.

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Showpad accelerates data maturity to unlock innovation using Amazon QuickSight

AWS Big Data

Showpad built new customer-facing embedded dashboards within Showpad eOSTM and migrated its legacy dashboards to Amazon QuickSight , a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale.

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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

They are used in everything from robotics to tools that reason and interact with humans. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. Increase trust in AI outcomes.

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