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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

Flipboard

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. Create dbt models in dbt Cloud.

ETL 134
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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. It integrates seamlessly with other AWS services and supports various data integration and transformation workflows.

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Understanding Business Intelligence Architecture: Key Components

Pickl AI

Summary: Understanding Business Intelligence Architecture is essential for organizations seeking to harness data effectively. This framework includes components like data sources, integration, storage, analysis, visualization, and information delivery. What is Business Intelligence Architecture?

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Ways Big Data Creates a Better Customer Experience In Fintech

Smart Data Collective

To ensure their customers have a satisfactory experience, financial businesses will use big data analytics to tweak their services across various platforms to suit a customer’s needs. They will also use historical and real-time data to identify possible customer challenges.

Big Data 145
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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Ensure that data is clean, consistent, and up-to-date.

Analytics 203
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How to Effectively Handle Unstructured Data Using AI

DagsHub

Word2Vec , GloVe , and BERT are good sources of embedding generation for textual data. These capture the semantic relationships between words, facilitating tasks like classification and clustering within ETL pipelines. Multimodal embeddings help combine unstructured data from various sources in data warehouses and ETL pipelines.

AI 52
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Access Amazon Redshift Managed Storage tables through Apache Spark on AWS Glue and Amazon EMR using Amazon SageMaker Lakehouse

Flipboard

Data environments in data-driven organizations are changing to meet the growing demands for analytics , including business intelligence (BI) dashboarding, one-time querying, data science , machine learning (ML), and generative AI.

AWS 132