Remove Cost-Benefit Remove Data Processing Remove Metadata Remove Structured Data
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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

The following diagram illustrates the different pipelines to ingest data from various source systems using AWS services. Data storage Structured, semi-structured, or unstructured batch data is stored in an object storage because these are cost-efficient and durable.

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Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS

AWS Big Data

Spark SQL is an Apache Spark module for structured data processing. FINRA centralizes all its data in Amazon Simple Storage Service (Amazon S3) with a remote Hive metastore on Amazon Relational Database Service (Amazon RDS) to manage their metadata information. or later installed. or later installed.

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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Within the context of a data mesh architecture, I will present industry settings / use cases where the particular architecture is relevant and highlight the business value that it delivers against business and technology areas. Data and Metadata: Data inputs and data outputs produced based on the application logic.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

The data volume is in double-digit TBs with steady growth as business and data sources evolve. smava’s Data Platform team faced the challenge to deliver data to stakeholders with different SLAs, while maintaining the flexibility to scale up and down while staying cost-efficient.