Name: AWS Data Exchange
Rating: 10 (9 reviews)
Author: Amazon AWS

Help Desk

Web and Video Conferencing

Customer Support

Augmented Reality Development

Performance Testing

Development

School Management

Education

Business Intelligence (BI)

Collaboration

Data Analytics  and BI Services

Data Discovery and Visualization

Digital Rights Management (DRM)

Document Management

Enhanced 911 (E911)

Enterprise Generative AI

Integrated Workplace Management (IWMS)

Payment Facilitation

Enterprise

Accounting

Trust Management

Finance and Accounting

Applicant Tracking

Corporate Learning Management

Corporate Volunteering

Employee Monitoring

HR Management

Payroll

Recruitment Agency

Stock Option Plan Administration

Talent Intelligence

Talent Management

Video Interview

Workforce Analytics

Workforce Management

Human Resources

3D Printing

AI Governance

Application Performance Management (APM)

Cloud Migration

Cloud Storage

DevSecOps

Firewall

Fraud Detection

Hadoop-Related

Integration Platform as a Service (iPaaS)

Network Performance Monitoring

Product Implementation Services

Robotic Process Automation (RPA)

Telecom Expense Management (TEM)

Web Scraping

Zero Trust Security Solutions

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Appointment Scheduling

Audience Engagement

Content Management

Cross-Channel Campaign Management

Email Marketing

Email Testing

Employee Advocacy

Enterprise Marketing Management

Marketing Automation

Social Media Advertising

Social Media Management

Survey & Forms Building

Web Analytics

Wholesale Marketplace

Marketing

Job Site Management

Project Management

Waste Management

Professional Services

Customer Relationship Management (CRM)

Social Commerce

Sales

Cloud Access Security Brokers

Secure Access Service Edge (SASE)

User and Entity Behavior Analytics (UEBA)

Security

Camp Management

Digital Forensics

Estate Planning

Vertical-Specific

Find top rated software and services based on in-depth reviews from verified users. 400+ software categories including PaaS, NoSQL, BI, HR, and more.

Snowflake

Snowflake Computing

Oracle Data Integrator (ODI)

Oracle

SAP HANA Cloud

Microsoft Azure

Microsoft

Informatica PowerCenter (legacy)

Discontinued Products

Matillion

Qlik Replicate

Qlik

Altova MapForce Server

Altova

Google App Engine

Google

Skyvia

Devart

### Data Integration and Maintenance
Users generally find AWS Data Exchange's data integration and maintenance capabilities to be a strong point. They appreciate the ease with which the platform allows for the maintenance of data, making it simple to analyze and share information efficiently. Additionally, users highlight the convenience of integrating third-party data sources within the platform, enhancing the overall data management process. The service's ability to streamline workflow maintenance and support data maintenance for large organizations is also commended. Furthermore, the secure and compliant nature of AWS Data Exchange, along with its integration with various tools and services, contributes to its appeal for users seeking reliable data integration and maintenance solutions.

### Data Providers and Sources
Users appreciate the ease of finding, subscribing to, and utilizing third-party data through AWS Data Exchange. The platform's secure and compliant nature, coupled with integrated tools and services, enhances the overall experience for customers like Capgemini and Goldman Sachs. The consolidated billing and subscription management further streamline the process, making it a valuable resource for accessing diverse data sources across various industries.

### User Experience and Interface
Some users find AWS Data Exchange's user experience and interface to be intuitive and efficient, praising its ease of navigation and quick access to information. However, others express frustration with the clunkiness of the system, citing missing essential functionalities, confusing UX bugs, and unhelpful support interactions. The lack of clarity on product attributes, fake information provided by sellers, and difficulties in payment processing contribute to a mixed sentiment towards the platform's user experience and interface capabilities.

### Stakeholder Collaboration
Users have expressed a positive sentiment towards AWS Data Exchange's stakeholder collaboration feature, highlighting its effectiveness in granting permission control to different stakeholders for accessing files. The ability to manage various stakeholders' actions based on their specific requirements has been a notable advantage for organizations utilizing the platform. While there may be room for improvement in certain aspects, overall, users appreciate the functionality that AWS Data Exchange offers in facilitating collaboration among diverse stakeholders within an organization.

### Documentation and Support
Users have expressed frustration with the clunkiness of the system, lack of essential functionalities, and numerous UX bugs that hinder the accurate representation of products. The absence of clear documentation and support has left users feeling lost and unproductive when seeking assistance from the AWS team. Despite some positive feedback on resolving pain points, the steep learning curve and inadequate documentation have been highlighted as significant drawbacks. The overall sentiment leans towards dissatisfaction with the documentation and support provided by AWS Data Exchange.

AWS Data Exchange is an integration for data service, from which subscribers can easily browse the AWS Data Exchange catalog to find relevant and up-to-date commercial data products covering a wide range of industries, including financial services, healthcare, life sciences, geospatial, consumer, media & entertainment, and more.

Astera Data Pipeline Builder is a no-code solution for designing and automating data pipelines. It allows users to read and write data across various file formats, databases, and applications. Users can execute ETL and ELT pipelines manually, schedule automated reruns, or integrate them into broader data management processes.

Centerprise Enterprise

Astera Data Pipeline Builder (Centerprise)

Toad Data Point is a cross-platform, self-service, data-integration tool that simplifies data access, preparation and provisioning. It provides data connectivity and desktop data integration, and with the Workbook interface for business users, it provides simple-to-use visual query building and workflow automation.

Base Edition

Pro Edition

Toad Data Point

AWS Data Exchange

Data integration involves combining data residing in different sources and providing users with a unified view of these data.

Data Integration

Likelihood to Recommend

Likelihood to Renew

Data Source Connection

Data Modeling

Data Governance

Connect to traditional data sources

Connecto to Big Data and NoSQL

Data model creation

Metadata management

Business rules and workflow

Testing and debugging

Integration with data quality tools

Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce platform.

Founded by Jeff Bezos, the Amazon.com website started in 1995 as a place to buy books because of the unique customer experience the Web could offer book lovers. Bezos believed that only the Internet could offer customers the convenience of browsing a selection of millions of book titles in a single sitting. During the first 30 days of business, Amazon fulfilled orders for customers in 50 states and 45 countries - all shipped from his Seattle-area garage.

Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world.

Amazon AWS

Ability to connect to multiple data sources

Ability to connect to traditional data sources like relational databases, flat files, XML files and packaged applications

Ability to connect to non-traditional data sources like Hadoop and other big data technologies, and NoSQL databases

Data Transformations

Data transformations include calculations, search and replace, data normalization and data parsing

Simple transformations

Simple data transformations are calculations, data type conversions, aggregations and search and replace operations

Complex transformations

Complex data transformations are data normalization, advanced data parsing, etc.

A data model is a diagram or flowchart that illustrates the relationships between data

Ability to create and maintain data models using a graphical tool to define relationships between data

Automated discovery of metadata with ability to synchronize and share metadata with other tools like Master Data Management

Ability to define and manage business rules and workflows

Collaboration is enabled by a shared repository of project information and metadata

Tool to debug and tune for optimal performance

Data governance is the practise of implementing policies defining effective use of an organization's data assets

Integration with tools for cleansing, parsing and normalizing data according to business rules

Integration with MDM tools

Integration with master data management tools to ensure data consistency across the organization

General Manager of Product-Led Growth

AWS Data Exchange 2022-11-21 11:57:31

Lead Consultant - Technology

AWS Data Exchange 2021-05-18 08:34:16

TrustRadius is a technology and business research firm based in Austin, Texas. The company is known as a review platform for verified B2B technology and software reviews through a proprietary algorithm and human verification.

TrustRadius

Data sources

Tracking data

Data services

Ability to create

Amount of data

Ability to integrate

Payment plans

Home

Data Integration Tools

We wanted to use AWS Data Exchange to list, sell and deliver our dataset in the open market. We have roughly 22 datasets that cover specific topical areas and industries. We update these sets on a monthly or quarterly basis depending on the data.

Allow you to make private transactions of data
Organize your datasets
Provide custom legal data services agreements

Poor transparency for sellers
Little verification of accounts requesting subscriptions
Confusing, buggy and misleading UX
Very poor development focus, roadmap and investment in the product
Bad experience for buyers of the data
Poor account service

AWS Data Exchange required a lot of time to setup and was hard to QA
We have had a lot of traffic flow to ADX with no conversion.
We had bad transactions because of compromised accounts, but AWS doesn't provide sellers with enough information/verification to trust subscription request
Buggy user experience so there have been erroneous details about our listings
Confusing documentation that is often not detailed enough or erroneous

Data delivery
Payment processing
Marketing and advertising

We use AWS Data Exchange as a straightforward solution to publish datasets from our healthcare solutions platform. This is a great way to get simulated datasets that we generate using machine learning methodologies out to potential clients, and to encourage the various partnerships we have with research divisions at universities that use datasets generated by our organization. Being able to point AWS Data Exchange at existing data sources such as AWS S3 and AWS Redshift has really helped us to simplify the process of delivering data to our clients and users.

Simplified data delivery
Ability to create any amount of data products
Ability to integrate payment plans with data products
Tracking data downloads and users
Integration with other AWS data services

Integration with more data sources
Ability to deliver data to clients without AWS accounts
Inclusion of direct data downloads in addition to asynchronous methods

Reduced time to publish datasets for sale by more than 80%
Increased net profit from dataset sales by ~10%
Reduced data delivery time to clients by 15%

AWS CloudFormation, AWS CodeDeploy, AWS CodePipeline, AWS Lambda, PyCharm, Jupyter Notebook, Docker, AWS Elastic Beanstalk

AWS Data Exchange

Overview

What is AWS Data Exchange?