Remove Business Intelligence Remove Data Analytics Remove Data Transformation Remove Data Warehouse
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Create a modern data platform using the Data Build Tool (dbt) in the AWS Cloud

AWS Big Data

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. dbt emerged as the perfect choice for this transformation within their existing AWS environment.

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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

For files with known structures, a Redshift stored procedure is used, which takes the file location and table name as parameters and runs a COPY command to load the raw data into corresponding Redshift tables. We encourage you to explore Redshift Serverless with CARTO for analyzing spatial data and let us know your experience in the comments.

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The Best Data Management Tools For Small Businesses

Smart Data Collective

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

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Transforming Big Data into Actionable Intelligence

Sisense

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data analytics case study: SkullCandy.

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Enable data analytics with Talend and Amazon Redshift Serverless

AWS Big Data

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Prerequisites To complete the integration, you need a Redshift Serverless data warehouse.

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7 key Microsoft Azure analytics services (plus one extra)

CIO Business Intelligence

And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done. For many enterprises, Microsoft Azure has become a central hub for analytics. The reason Azure has so many analytics services is so you can build your entire stack there.

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How GamesKraft uses Amazon Redshift data sharing to support growing analytics workloads

AWS Big Data

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.