Sign in Agent Mode
Categories
Your Saved List Become a Channel Partner Sell in AWS Marketplace Amazon Web Services Home Help

Reviews from AWS customer

7 AWS reviews

External reviews

98 reviews
from and

External reviews are not included in the AWS star rating for the product.


3-star reviews ( Show all reviews )

    Legal Services

Understanding the value of a data catalog

  • November 02, 2023
  • Review provided by G2

What do you like best about the product?
Support for wide range of platforms to pull in our enterprise data. Ability to customize the end user portal to hide noise from actionable insights
What do you dislike about the product?
Mostly wonder if the effort to maintain an accurate data catalog will be worth the business value of the information
What problems is the product solving and how is that benefiting you?
Standardizing our metric definitions and building trust in our data


    reviewer2281572

The solution enables users to customize templates, but it is expensive, and the interface is not user-friendly compared to some of the other products in the market

  • October 25, 2023
  • Review provided by PeerSpot

What is most valuable?

We can use the tool to put additional information about things. People can go through articles and get detailed knowledge. We can also create queries. We can customize templates based on our use cases. We can use API. We can create forms for the user.

What needs improvement?

It was not very clear how to connect to databases. The interface is not user-friendly. Some things in the interface must be made user-friendly. Some features are quite technical. A non-technical user might find the tool difficult to use.

For how long have I used the solution?

I have been using the solution for one or two months.

Which solution did I use previously and why did I switch?

I used OvalEdge two years ago. A non-technical person also can use OvalEdge quite easily. It enables users to connect to a database, crawl, and extract the metadata. It was not quite easy to do the same in Alation Data Catalog. OvalEdge is quite user-friendly. We can create rules behind the data and add data dictionaries and glossaries.

In Alation, we can write a complete article for a specific object and link it to different tables and columns so the user can easily navigate to a particular object or table. OvalEdge is cheaper, though.

What's my experience with pricing, setup cost, and licensing?

The solution is a little expensive.

What other advice do I have?

I have gone through the training for Alation Data Catalog. Overall, I rate the product a seven out of ten.


    Government Administration

Powerful and simple to use Metadata Catalog Tool

  • May 23, 2023
  • Review provided by G2

What do you like best about the product?
Ease of Use. Caters for a customised user requirement implementation. Good product support.
What do you dislike about the product?
Not historically focused on UK Public Sector and unawareness of the culture challenges coupled with disparate source system landscape to implementing a Metadata Catalog Tool.
What problems is the product solving and how is that benefiting you?
Lack of awareness on what data is available in the organisation, who owns it, who manages it, repeated data discovery exercises for the same data, lack of metadata accuracy, lack of organisational business glossary and management thereof


    Mayank K.

Great tool for analytics

  • March 29, 2022
  • Review provided by G2

What do you like best about the product?
Tool helps in getting the data processing fast and a great user friendly tool
What do you dislike about the product?
It has data limitations capacity. Sometimes does not respond when processing large amount of data.
What problems is the product solving and how is that benefiting you?
Tool is similar to other data processing software but data processing is really faster as compared to other softwares
Recommendations to others considering the product:
Its a great differentiated software as compared to other softwares in the market. Very good software when processing large amount of data for ML algorithms.