Streamlined metadata workflows have saved time and now support faster data-driven decisions
What is our primary use case?
My main use case for Atlan is that it is very easy and integrable with other data sources, which is very convenient and time saving. By switching to Atlan, we have increased our productivity and saved a lot of business time. Our team, whether technical or non-technical, adapted to Atlan very quickly because of its simple user interface.
A quick, specific example of how my team uses Atlan day-to-day is that we introduce some new technologies in our system and every time integrating those tools or technologies with Atlan is much easier and smoother.
My team uses Atlan to define a flexible set of metadata, including measuring the quality of said data. Atlan is also a partner of ours, so we use it to integrate with our own tools. It also enables the team to automate manual and high-risk tasks and to make them error-free as much as possible.
What is most valuable?
The best features Atlan offers are that it is very easy to extract and modify data. We can perform very quick and smooth integration. Its open-source framework provides extension and capability to the API it uses. It has a user-friendly interface, easy access to data, data tables, and a lineage feature.
Atlan provides extensive and seamless integrations, a ton of automation, and an extremely user-friendly and intuitive interface to navigate.
Atlan has impacted my organization positively because it has been very helpful. Atlan has certainly saved time and money by consolidating our metadata sets. Integration with Amazon and Tableau have definitely sped up our time to value.
We have been able to save time and money by consolidating our data by at least 45%.
What needs improvement?
Atlan can be improved because API documentation could be enhanced.
I wish the support team could be quicker in their response time.
The reason why I rated it a nine is that it has improved our compliance and risk management. What could have made it a perfect ten for me is if it had improved API documentation and if the support could be much quicker in their response time. It is also very easy to adopt and has good pricing.
For how long have I used the solution?
I have been using Atlan for about six years.
What other advice do I have?
My advice to others looking into using Atlan is that it is a well-suited tool because it is very cost-effective and easy to use. It also has robust functionality for the quality management of metadata sets. The most helpful thing here is all the dashboards that provide visibility in one place. In my experience, it might be less suited for collaboration across teams.
Atlan is very easy to use, and anyone could pick it up relatively quickly. I rated this product a nine out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Automation has transformed data quality workflows and now saves significant time and cost
What is our primary use case?
My main use case for Atlan is to define a flexible set of metadata, including measuring the quality of said data. Atlan is also a partner of ours, so we use it to integrate with our own tool. It also enables our team to automate manual and high-risk tasks to make them error-free as much as possible and save time. In terms of scope, I only know that our Sales, CSM, and CX teams use it for similar uses. Our business may use it to a larger scope than that in the future.
What is most valuable?
A quick specific example of how our team uses Atlan to automate a manual or high-risk task is the robust functionality for the quality management of metadata sets. The most helpful thing here is all the dashboards that provide visibility in one place. We use this tool because it is very easy and integrable with other data sources, which is very convenient and time-saving. By switching to Atlan, we have increased our productivity and saved a lot of business time through automation. My team, whether technical or non-technical, adapted Atlan very quickly because of its simple and intuitive user interface.
The best features Atlan offers include the ease to extract and modify the data. We can do very quick and smooth integration. It is an open-source framework that provides extension capability to the APIs it uses.
Tons of automation help to automate tedious and time-consuming tasks, thereby reducing error and saving time and cost. It is extremely user-friendly and intuitive to navigate, especially the user interface.
Atlan has positively impacted my organization by saving time and money while consolidating our metadata sets. Integration with Amazon and Tableau have definitely sped up our time to value.
We have saved fifty-five percent of our time through the automation of tedious and time-consuming tasks. Extraction of data is easy. In this data catalog solution, data modification is really simple and easy. Integration with other software is very seamless and easy, thereby simplifying our workflow.
Atlan is very scalable and helps to grow our organization while catering to our needs.
It enables the team to automate manual and high-risk tasks to make them error-free as much as possible and save time and cost. It is a very cost-effective tool that should be highly adaptable and usable in any organization.
What needs improvement?
Atlan can be improved by enhancing their support process by reducing the resolution time.
They have really bad and incomplete documentation, so they should work on the documentation as well, especially to help new users who are onboarding to make their process more intuitive and smooth.
For how long have I used the solution?
I have been using Atlan for five years.
What do I think about the stability of the solution?
Atlan is stable; I have not experienced any downtime.
What do I think about the scalability of the solution?
Atlan is very scalable and helps our organization to grow while catering to our needs.
How are customer service and support?
Customer support for Atlan is not so proactive. They should improve their proactiveness to be more proactive and responsive.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
Previously, I used Informatica, specifically Informatica Application ILM.
I decided to switch from Informatica to Atlan because the other tools were solid. We ultimately ended up going with Atlan for this reason: it improved our compliance and risk management. It is easy to adopt and has good pricing. It seemed to have the most robust functionality, especially in terms of integration. It is easy to use, anyone could pick it up relatively quickly, and the cost was affordable.
How was the initial setup?
We purchased Atlan through the AWS Marketplace.
What was our ROI?
Atlan has certainly saved time and money by consolidating our metadata sets.
What's my experience with pricing, setup cost, and licensing?
My experience with pricing, setup cost, and licensing is that the licensing cost is a bit flexible but not affordable for smaller organizations. It might be way out of their budget, but it is very affordable for medium and large enterprises.
Which other solutions did I evaluate?
Before choosing Atlan, I evaluated Talend Data Catalog.
What other advice do I have?
Day-to-day, we introduce some new technologies in our system, and every time we integrate those tools with Atlan, it is way easier and smoother. I would rate this review as a nine out of ten.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Great cataloging and best-in-class lineage, but support response can be slow
What do you like best about the product?
We can catalog tables and reports, the lineage feature is best
What do you dislike about the product?
May be the support for the tool. The repsonse takes time
What problems is the product solving and how is that benefiting you?
We are using mainly to find lineage through all our data warehouse.
It makes debugging easy
Exceptional Data Discovery, Data Governance, and Data Quality With Atlan
What do you like best about the product?
Atlan comes with great data discovery features and it ensures smooth data collaboration.
With the tool, finding, sharing and understanding data is always easy.
I like how easy Atlan makes it to maintain data quality and governance.
It comes with amazing machine learning features and amazing data AI features.
I like that Atlan supports modern data architecture.
What do you dislike about the product?
No flaws to report considering Atlan has met our needs more so in data governance and data quality.
What problems is the product solving and how is that benefiting you?
Atlan has been very helpful in maintaining data quality and handling data governance thanks to the amazing AI features and machine learning.
Improved data discovery has reduced redundant ingestion and now supports governed asset management
What is our primary use case?
Atlan is used as a data catalog and a data governance tool. The primary idea for implementing Atlan for data cataloging in day-to-day work was to create a business data catalog to support asset discovery and management.
What is most valuable?
Atlan offers excellent features including support for many different active metadata, such as lineage, which allows visibility into how an asset has been generated.
Active metadata and lineage features help quickly understand if an asset already exists, who the data steward is for that asset, and provide complete visibility on available fields and other technical aspects regarding the asset.
Atlan has positively impacted the organization since it helps in discovering already available assets, allowing for reduction of redundant ingestion of external data and reduction of time to market for any project.
What needs improvement?
Atlan can be improved by integrating agents that can support users in finding assets of interest.
For how long have I used the solution?
Atlan has been used for one and a half years.
What other advice do I have?
I rate Atlan overall a nine out of ten. I choose nine out of ten because even though Atlan is a very good product, it can be further improved. For others looking for a very complete data catalog tool with many features that can support data discovery, lineage, and more, I suggest choosing Atlan.
Which deployment model are you using for this solution?
Private Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Transforms Data Collaboration with Ease and Efficiency
What do you like best about the product?
What I appreciate most about Atlan is how it transforms working with data into a truly collaborative and seamless experience. By bringing together people, data, and context in a single platform, it enables teams to genuinely understand and trust their data. I find it incredibly easy to locate what I need, document my work, and maintain organization without the usual confusion. Atlan is clearly designed to make data serve people, rather than forcing people to adapt to data. Its smooth integration with modern tools allows teams to work more efficiently, and it makes the entire data process feel more human, transparent, and enjoyable.
What do you dislike about the product?
One aspect I find challenging about Atlan is that it can sometimes feel overwhelming due to the sheer number of features and configuration options. For newcomers, the learning curve is quite steep before you can fully appreciate its value. There are also times when performance slows down, especially when handling very large datasets or complex integrations. Additionally, I would appreciate more flexibility in some customization options to better accommodate specific team workflows. However, these concerns are relatively minor compared to the overall experience—once you become familiar with the platform, Atlan proves to be both powerful and enjoyable to use.
What problems is the product solving and how is that benefiting you?
Atlan addresses one of the most significant challenges in the data world: the lack of visibility, collaboration, and trust in data. By bringing together scattered data assets, documentation, and context into a single, unified workspace, it becomes much easier to discover, understand, and confidently use data without wasting time searching or doubting its accuracy. Personally, Atlan has made collaboration across teams more efficient, reduced reliance on individual expertise, and enhanced overall data quality. It has also simplified onboarding for new team members and sped up decision-making by ensuring everyone has clear and reliable access to the right data when they need it.
Magically Boosts Productivity and Workflow
What do you like best about the product?
It significantly enhances productivity, streamlines workflow, and makes implementation across the business remarkably easy, almost like magic!
What do you dislike about the product?
The customer support isn't particularly impressive, but it is still an improvement over what I've experienced with other competitors.
What problems is the product solving and how is that benefiting you?
Integration of the source data made seamless and data privacy/storage are top notch that I can sleep without any issues.
Gratitude towards Atlan
What do you like best about the product?
Its user friendly data catalog and it is very supportive and collaborative.
What do you dislike about the product?
Limited customization for UI components.
What problems is the product solving and how is that benefiting you?
Ensuring good quality data.
Has struggled to meet business needs but supports technical data exploration and transparency
What is our primary use case?
I have been using
Atlan for two years.
My main use case for Atlan includes data catalog, business glossary, import-export, data lineage, lineage import-export, and lineage generator, as I was the intense tester of Atlan.
In my day-to-day work, I use Atlan to analyze databases to find lineage or try to import business glossaries from Excel from several business sources, importing them into Atlan or trying to visualize the lineage, which is exactly what the customer needed. Importing a business glossary connects business terms with some IT tables and columns and makes it visible. What is unique about my main use case is that I was heavily involved in the import-export formatting of data, trying to automate some import-export, figuring out how the templates work for export-import, how the specific import-export workflows run in Atlan, what failures can happen, the uniqueness of data, and finding matching partners in lineage cases.
What is most valuable?
The best features Atlan offers for me include reading the data, having the interfaces, and reading the data from tables from different sources, performing automated import exports, and connecting sources to IT systems, which I consider the biggest strength of Atlan.
The interfaces and automated imports have helped me with transparency, as we have different sources from different techniques such as DBT, Snowflake, and other regular databases, making it effective to connect these sources and navigate through them, filter them, and enrich the data with additional meter information.
Atlan has positively impacted my organization by helping the business people use it to understand where the data is, what meta information is, and attempt to assume the roles of a data owner and a data steward, which was new for them. They find it much easier to search and navigate the data and better understand the data.
The change has affected my team's productivity and collaboration by reducing the time of finding the right data, navigating, and creating a new report, which helped the business people understand their jobs. When creating a new data governance team, it is a challenge for people to assume these roles, and using Atlan was a significant advantage in helping them identify what the role is and begin to assume it.
What needs improvement?
Atlan can be improved by concentrating more on business data since it is developed from developers for developers, and it needs to be more business relevant. For instance, when re-importing data model diagrams, Atlan provides some diagram automation that is not connected to the business glossary, which I consider a significant fault. Atlan needs to improve by focusing more on the business side of data, not only on technical aspects.
If you want to focus on technical considerations, it would be beneficial to have an interface with a real business data modeling tool such as Erwin or other business data tools, since data modeling is not the same as Draw.io. Additionally, Atlan can improve its workflows, which are hard to understand. Working with templates, Excel import, export, and running automations is not self-explanatory, and you always need help from Atlan support team. If business people want to use it and run their own reports, it must be easier to customize for their business needs.
What do I think about the stability of the solution?
What do I think about the scalability of the solution?
I did not hear anything negative regarding Atlan's scalability. We started with a small group and brought business teams or new members on board, and there were no issues at all. Scalability is perfect.
How are customer service and support?
I can only share positive results about Atlan's customer support. They were keen on helping us, providing answers in a very comfortable time frame, making it quick and easy, and they always tried to offer the best solution even for our very customized requirements.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I have experience with many modeling tools including DataSpot,
ARIS, and Enterprise Architect, but those are not really data catalog tools. Depending on the purpose, it is important to start from the business side for implementations related to data understanding and data catalog, rather than from the technical side.
Which other solutions did I evaluate?
Before choosing Atlan, there were other options such as
Collibra and Atlassian, but I was not involved in the proof of concept and we started working once Atlan was selected.
What other advice do I have?
For the user experience, it is sometimes tedious because when reading the source and finding the data tables, if I then try to find matching partners or visualize some lineages, it can be overwhelming. I need to either shrink the scope of my task, use lesser complexity, or use fewer tables to generate business values. Sometimes it can simply be overwhelming.
My advice for others looking into using Atlan is that they must be clear upfront about the purpose and scenario for which they want to use it. If they want to connect databases, read, surf, and do that, then I would recommend it. However, if they want to start a data governance organization or business understanding, that would be a totally different story because Atlan has strengths in technical connections.
Atlan should be made livable for business people. It should not be solely from developers for developers, as there is a vast range of business users who are happy if they can read Excel sheets but do not have knowledge about XML data formats and other technical considerations. If you want to expand your customer range, Atlan should learn business language and not focus so much on technical language, making it usable for business professionals. I rate this product a five out of five.
Atlan _review
What do you like best about the product?
The product stands out for its ease of use, making it accessible even for those who are not very tech-savvy. Implementation was straightforward, and I appreciated how the features were both comprehensive and practical. Integration with other tools was smooth, which made the overall experience even better.
What do you dislike about the product?
The AI capabilities are limited, and the automation feels quite rigid. Additionally, it lacks features for managing tasks across multiple teams.
What problems is the product solving and how is that benefiting you?
The platform offers data discovery and cataloging features, which help in organizing and managing information efficiently. Its automation and integration capabilities further streamline workflows, making it easier to connect different systems and reduce manual effort.
