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AWS Glue

AWS Glue is a fully managed ETL service provided by Amazon Web Services (AWS). It is designed to prepare and transform data for analytics.

$55.00

AWS Glue is a fully managed ETL service provided by Amazon Web Services (AWS). It is designed to prepare and transform data for analytics.

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Pricing Table

Features

Small


$9,500

/ total

Initial Business Idea Analysis and Documentation

Medium


$20,000

/ total

Solution Analysis Vision & Scope

Large


$35,000

/total

Solution Analysis Vision & Scope (large-scale)

Discovery Timeline

up to 3 weeks

from 4 to 7 weeks

from 6 to 9 weeks

Define Business goals and objectives of the expected product

Requirements Elisitation Sessions (stakeholders interviews, workshops)

up to 5 workshops

up to 7 workshops

up to 9 workshops

Requirements Modeling and Documentation

Quality Attributes Workshop

Business Requirements Specification

Competitor Analysis

Product Succcess Metrics

Functional Decomposition

Key Business Processes & Sequence Diagrams

Non-Functional requirements analysis and documentation

Software Architecture Vision and High-level Design

Entity Relationship Diagram

Technology Stack

Technical Risks Identification

Architecture decisions report

Wireframes

up to 3 core user flows

up to 10 core user flows

up to 15 core user flows

Product Information Architecture

Business Model Canvas

Customer Journey Map

Value Proposition design Workshop

Delivery Time

Description

AWS Glue is a fully managed ETL service provided by Amazon Web Services (AWS). It is designed to prepare and transform data for analytics. It integrates seamlessly with other AWS services.

Key features:

Serverless architecture.
Scalable data integration.
Automated schema discovery.

Pros and cons: It supports a wide range of data formats and provides automated data cataloging. However, the service has a steep learning curve for beginners and can be costly for complex ETL jobs, especially outside of the AWS environment. So, if you are not heavily invested in the AWS ecosystem, consider a more user-friendly data integration solution.

Best use case scenario: Large-scale ETL processes within the AWS ecosystem.

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