We are a consulting company, and we propose Atlan as one of the tools in the market. We inform clients that if they are considering a data catalog, they can also consider Atlan. We evaluate it for them, determining whether it would make sense for their organization.
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Powerful platform for data engineers, but lacking intuitiveness for business users
What do you like best about the product?
- Standardized data contracts using YAML templates
- Compatibility with open source frameworks like Apache Spark, Airflow
- Great technical catalog for data engineers
- Lineage packages and libraries
- Compatibility with open source frameworks like Apache Spark, Airflow
- Great technical catalog for data engineers
- Lineage packages and libraries
What do you dislike about the product?
- Not user friendly for line of business users
- UI / UX was perceived to be too technical
- Great technical catalog but doesn't cover business governance requirements like CDEs
- UI / UX was perceived to be too technical
- Great technical catalog but doesn't cover business governance requirements like CDEs
What problems is the product solving and how is that benefiting you?
- Data Lineage Tracking
- DataOps Monitoring
- Data Contracts Enforcement
- DataOps Monitoring
- Data Contracts Enforcement
Atlan for modern data management
What do you like best about the product?
Our experience with Atlan has been exceptionally positive, from initial exploration and technical evaluation to implementation and ongoing operational support. We included Atlan as part of our data infrastructure due to its intuitive user interface, robust product features, and forward-looking vision. Atlan's compatibility with the rest of our modern data stack (Snowflake, dbt, Sigma Computing) and other enterprise tools such as Slack, Google Workspace, and Chrome was a key factor, too. The Atlan team provided ample opportunity to carry out a Proof of Concept (POC) and Proof of Value (POV), which included live demonstrations of functionalities to the various data stakeholders. Additionally, Atlan's pricing and support model were both reasonable and adaptable.
Setting up the platform was swift, with a few hours of onboarding calls spread over a week. We could quickly run scans on our Snowflake instance and set up integrations with other platforms like dbt. Later, when support for Sigma Computing was introduced, we could integrate the same on our own. Features such as web search of metadata and detailed column-level lineage for root cause and impact analysis were an instant hit with our data power users.
The Atlan customer success team was meticulous in providing us with the necessary support to improve the adoption and engagement on the platform. They consistently strive to understand our specific use cases, deliverables, and business outcomes to provide optimal support. We appreciate how the Atlan team has supported us so far with active metadata management and helping improve the governance of our data and machine learning products.
Setting up the platform was swift, with a few hours of onboarding calls spread over a week. We could quickly run scans on our Snowflake instance and set up integrations with other platforms like dbt. Later, when support for Sigma Computing was introduced, we could integrate the same on our own. Features such as web search of metadata and detailed column-level lineage for root cause and impact analysis were an instant hit with our data power users.
The Atlan customer success team was meticulous in providing us with the necessary support to improve the adoption and engagement on the platform. They consistently strive to understand our specific use cases, deliverables, and business outcomes to provide optimal support. We appreciate how the Atlan team has supported us so far with active metadata management and helping improve the governance of our data and machine learning products.
What do you dislike about the product?
A strong product roadmap backs the vision, but the communication regarding the upcoming features and releases can be better. The concepts of Personas and Purpose overlap, and explaining them to most stakeholders is difficult.
What problems is the product solving and how is that benefiting you?
Helping find information about data is easier in a self service way that reduces dependency on data engineers and helps them focus on writing code. The lineage helps during impact analysis and troubleshooting. Establishing a better data governance is easier with a tool like ATlan.
Using Atlan for Data tagging/Classification
What do you like best about the product?
The ability to apply definitions and tags for almost any data asset is useful, especially the feature to attach existing documentation as a resource. Great search feature, and ability to propagate tags downstream from objects.
What do you dislike about the product?
The UI is sometimes difficult to navigate, and there are some screens that may be more suitable to view as a table. There's also sometimes a steep learning curve to go from basic read-only use (or single asset management), to enabling mass-tagging/documentation efforts.
What problems is the product solving and how is that benefiting you?
Atlan is supporting our initiative to tag and classify all sensitive data in our source system and downstream applications. Being able to propagate tags and view lineage has been really useful.
Integration with communication platforms streamlines data access
What is our primary use case?
What is most valuable?
The best feature of Atlan is its integration with communication platforms like Microsoft Teams and Slack, so business users don't have to go into a data catalog to see metadata about data assets. This integration feature is the coolest thing about Atlan. The ML capabilities that suggest data classifications and provide data descriptions are also impressive.
What needs improvement?
One of the main areas for improvement is its governance capabilities. Atlan supports only basic out-of-the-box workflows, and it becomes challenging to customize features like how data owners should approve access to data assets. Its performance is not optimal when dealing with larger datasets, particularly legacy data assets, as the performance declines when scanning datasets running in terabytes.
For how long have I used the solution?
I have done a couple of POCs using Atlan while working for a company. We were evaluating a few data catalogs, and we included Atlan as one of the prospects.
What do I think about the stability of the solution?
During our POC, the recently launched ML classification system was a hit-and-miss. However, the support team acknowledged it and since then, the feedback from various users indicates that the issues have been resolved, and it's now working well.
What do I think about the scalability of the solution?
Atlan integrates well with smaller datasets, making it suitable for agile companies. However, it struggles with performance when dealing with larger datasets, particularly those running in terabytes.
How are customer service and support?
During the POC, we had a dedicated account executive, and we received good support from them. They helped us navigate our challenges and brought in technical resources whenever required. There were instances when responses took longer than expected, but this could be attributed to us not being a full-time paid customer at that time.
How would you rate customer service and support?
Positive
How was the initial setup?
If implementing the cloud instance, the setup is straightforward and simpler than other tools I have experienced. However, placing it on-premises requires support from data engineering or technical associates.
What's my experience with pricing, setup cost, and licensing?
In comparison to established players like Collibra and Informatica, Atlan is cheaper. However, compared to the next generation of data catalogs like Castor, Atlan is pricier. For mid-sized organizations, Atlan provides a good pricing fit.
Which other solutions did I evaluate?
We evaluated Atlan alongside other data catalogs when working for a company.
What other advice do I have?
Atlan is an eight out of ten, primarily due to its need for improved governance features. If these features are enhanced, it is a ten on ten tool.
Atlan has unique ML/AI capabilities that aid engineering teams in documenting without having to start from scratch.
Additionally, its integration with communication platforms helps users understand context without accessing the data catalog directly.
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?
Other
Enhanced data management with intuitive data lineage and metadata visualization
What is our primary use case?
One of the primary use cases of Atlan is as an enterprise data catalog. It takes metadata from multiple types of source systems, such as Tableau and Google BigQuery. The platform helps surface everything into a unified data dictionary and data catalog.
How has it helped my organization?
From a business user's perspective, Atlan has reduced the need to bother subject matter experts by surfacing all data and context. It has significantly reduced instances of business users contacting technical SMEs with questions about data content, providing time savings from a human hours perspective.
What is most valuable?
As a senior analytics engineer, Atlan's ability to show end-to-end data lineage is the most important feature for me. It graphically displays the entire data flow, allowing me to understand the flow from source systems to Tableau, including the ability to see SQL scripts behind it and usage metrics. Its capability to automatically pull data descriptions and assign ownership are also noteworthy.
What needs improvement?
Certain UI changes could make Atlan more user-friendly. While they have an Excel add-in for interaction with Atlan, it's in its early stages and could be improved. Additionally, data observability capabilities could be enhanced to provide more alerts on stale or outdated data via communication tools like Microsoft Teams, Slack, or email.
For how long have I used the solution?
I have been using Atlan for almost a year now.
What do I think about the stability of the solution?
Generally, I find Atlan stable. There have been instances where new features temporarily degraded performance. They were quickly optimized by Atlan's engineering team.
What do I think about the scalability of the solution?
There have been no notable scalability issues with Atlan. Its cloud-native backend infrastructure is designed to scale and may require human intervention occasionally, but it handles scalability well.
How are customer service and support?
The customer service and support are pretty good. Any issues are addressed promptly by Atlan's team.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We looked at Google Cloud Platform's Dataplex. It wasn't fit for purpose because we needed an active metadata platform that could provide comprehensive data discovery and data dictionaries.
How was the initial setup?
The initial setup of Atlan was conducted as a minimum viable product, starting with basic capabilities and building up. From the user's perspective, it involved training a small community of super users to promote adoption.
What about the implementation team?
The implementation of Atlan required less than five people from different teams, mainly technical personnel.
What was our ROI?
It's difficult to quantify ROI at the moment due to our immature use of Atlan, however, it has reduced interruptions for technical queries significantly.
What's my experience with pricing, setup cost, and licensing?
The pricing model for Atlan is reasonable compared to other cloud-based platforms. There are different license levels, and we receive a discount on the unit price, making it very competitive.
Which other solutions did I evaluate?
We evaluated Google Cloud Platform's Dataplex, among other tools, yet chose Atlan for its comprehensive capabilities in data lineage and metadata management.
What other advice do I have?
I would recommend dedicated resources from the beginning, including a product manager, as it facilitates better planning and adoption of the solution.
Overall, I rate Atlan a nine out of ten. They continue to innovate and listen to customer feedback.
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?
Other
Intuitive comprehensive tool enhances metadata management but needs improved lineage capabilities
What is our primary use case?
Data governance is a broad area, and Atlas is used for various purposes including self-service discovery, lineage, root cause analysis, impact analysis, and capturing all the metadata.
What is most valuable?
Atlas is quite intuitive. In the market, tools like Informatica require multiple components, however, Atlas provides all capabilities within one tool. Its UI is appealing and intuitive.
Additionally, the AI part is integrated for enriching metadata engagement, making it a comprehensive tool.
What needs improvement?
The challenge is in the lineage, where it requires improvement. Atlas needs to capture areas where organizations use less known applications.
For how long have I used the solution?
I've used the solution for more than a year now.
What do I think about the stability of the solution?
The UI exposure is very good, but as you consume more resources from the infrastructural point, such as managing bulk metadata, you might need the support of an infrastructure team. This is where Atlas's product team can help by increasing resources.
What do I think about the scalability of the solution?
You can scale, but it's necessary to reach out to their architectural team. Out-of-the-box scaling capabilities are limited and defined as standard by Atlas for their clients.
How are customer service and support?
The support team can be improved, especially the ticketing system. Though the team's knowledge is satisfactory, the overall ticketing process requires enhancements.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
We evaluated other data governance tools before settling on Atlas.
How was the initial setup?
The initial setup doesn't take much time since it's a cloud platform. However, issues may arise with the lineage aspects that Atlas needs to address.
What's my experience with pricing, setup cost, and licensing?
Atlas is competitively priced compared to other data governance platforms like Collibra and Informatica. The only major drawback is its lack of an integrated data quality module.
Which other solutions did I evaluate?
We evaluated other data governance tools previously.
What other advice do I have?
For stability, I would rate relevant features at seven out of ten. Atlas is suitable for smaller to mid-size companies, however, for larger organizations with multiple ERPs and data lakes, it may present challenges.
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?
Other
Streamlined data discovery with cohesive glossary and lineage tracking
What is our primary use case?
We use Atlan as a data discovery tool for data assets in our organization. It is particularly valuable for its ability to serve as a business glossary and a metrics glossary.
Additionally, it helps in lineage tracking to find data sources and overall dataset schema and is used extensively for data quality checks.
What is most valuable?
Atlan is helpful for identifying datasets and discovering PI data, such as the classification levels of datasets (gold, silver, bronze). The tool facilitates easy navigation by keeping descriptions and source information in one place. It supports data glossary terms, which helps with understanding business terms.
What needs improvement?
One area that could be improved is the capability to find duplicates of datasets. This would allow users to identify and consolidate similar datasets, having one point of access for consistent data.
For how long have I used the solution?
I have been working with Atlan for about a year and a half.
What do I think about the stability of the solution?
Atlan is quite stable. I have never seen it crash, and it has always been available to meet our needs. This consistent availability ensures we can find the right dataset when needed.
What do I think about the scalability of the solution?
Regarding scalability, recent updates in Atlan have included data contracts and specification levels for datasets. The company has a good relationship with Atlan, which regularly visits our office to understand our needs. As a result, I would rate the scalability as nine.
How are customer service and support?
I have never spoken to technical support, as I have not experienced any issues that required their assistance.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
I am not aware of any previous solutions the organization used before Atlan.
What was our ROI?
It's challenging for me to comment on the ROI since I am just a user of Atlan and do not have visibility into metrics or financial improvements.
What's my experience with pricing, setup cost, and licensing?
I am not aware of the pricing or setup cost.
Which other solutions did I evaluate?
I am not aware of any other solutions that were evaluated.
What other advice do I have?
Overall, I rate Atlan as a ten out of ten. It is an excellent solution for data discovery and glossary needs. I suggest improving duplication detection for datasets as an enhancement.
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
Democratizing Data: How Atlan Encourages Organization-Wide Collaboration
What do you like best about the product?
Atlan’s user-friendly interface encourages engagement across the board, regardless of technical expertise. The data lineage feature provides a clear, visual layout of our data stack, which has been particularly helpful in onboarding new hires by giving them immediate insight into our data architecture. The glossary feature is crucial for establishing a common understanding of terms and metrics throughout the company, with the ability to assign ownership to these definitions. Linking glossary terms to related assets further reinforces this shared understanding and accountability.
What do you dislike about the product?
The integration with Teams could be more refined. Specifically, it would be beneficial if requests for approval could be directed to the appropriate data owner or individual, rather than just an administrator.
What problems is the product solving and how is that benefiting you?
We lacked a consolidated view of our overall data landscape, and there was a clear need to standardize corporate terminology and metrics with defined lines of responsibility. Atlan addressed these challenges by providing a unified platform that supports our data governance and operational goals.
Easy, Breezy, Data Governance
What do you like best about the product?
Having used other tools in this space Atlan has a much better administrative and user experience than other tools.
•It was easy to set up and integrate with our tech stack.
•Navigating it feels intuitive which is critical to a metadata management system you need to put in front of multiple user personas.
They are also developing at a rapid pace which features getting releases each week and an eagerness to hear/respond to feedback. Some of the newer features aren't perfect but they are generally equiavalent to competitors and at the pace of development I see they pulling ahead.
Support has been great - we actually get responses from people that want to help instead of it going into a black hole.
•It was easy to set up and integrate with our tech stack.
•Navigating it feels intuitive which is critical to a metadata management system you need to put in front of multiple user personas.
They are also developing at a rapid pace which features getting releases each week and an eagerness to hear/respond to feedback. Some of the newer features aren't perfect but they are generally equiavalent to competitors and at the pace of development I see they pulling ahead.
Support has been great - we actually get responses from people that want to help instead of it going into a black hole.
What do you dislike about the product?
Would like to see usage reporting built into the product to help tell the story on its value and ensure we are positively driving adoption. Right now this is only available from a 3rd party source which wasn't mentioned to us and we'd have to get approval to use.
What problems is the product solving and how is that benefiting you?
Its integrating metadata from multiple systems and exposing it to our users in a easy to consume way so its organized, Discoverable and trusted.
In general the experience is good in usability and could be improved in technical support
What do you like best about the product?
Its UX and its deployment added its data lineage and the easy integration with multiples sources.
What do you dislike about the product?
Its technical supports is to slow in the resolution and sometimes not very accurate
What problems is the product solving and how is that benefiting you?
Its resolve the data catalog and data lineage by organizin the company to self service information.
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