Data analysis for regulated industries

In recent years, the demand for business users to be able to consume, transform, model, and visualize large amounts of complex data from multiple heterogeneous sources has increased dramatically. To meet this demand in a cost-effective, scalable way, many large companies have benefitted from moving to cloud-based data platforms.

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Build event-driven data quality pipelines with AWS Glue DataBrew

Businesses collect more and more data every day to drive processes like decision-making, reporting, and machine learning (ML). Before cleaning and transforming your data, you need to determine whether it’s fit for use. Incorrect, missing, or malformed data can have large impacts on downstream analytics and ML processes. Performing data quality checks helps identify issues earlier in your workflow so you can resolve them faster. Additionally, doing these checks using an event-based architecture helps you reduce manual touchpoints and scale with growing amounts of data.

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Transform data and create dashboards using AWS Glue DataBrew and Tableau

With AWS Glue DataBrew, you can now easily transform and prepare datasets from Amazon Simple Storage Service (Amazon S3), an Amazon Redshift data warehouse, Amazon Aurora, and other Amazon Relational Database Service (Amazon RDS) databases and upload them into Amazon S3 to visualize the transformed data in a dashboard using Amazon QuickSight or other business intelligence (BI) tools like Tableau.

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