Easy to use
What do you like best about the product?
The tool is very intuative to navigate, making it so we don't have to do a lot of training for new users. Implimentation was also easy and their customer support has been great!
What do you dislike about the product?
The lack of flexibility around custom fields.
What problems is the product solving and how is that benefiting you?
We have a way for business users to easily document trible knowlage, link business terms to technical assets so people can self serve on knowing where in the database to get data and knowing the definitions of the data they are using. Allows our technical teams to have a diagram of how lineage.
Atlan - AI based metadata management for datalakes
What do you like best about the product?
Atlan provides detailed metadata on data plarforms, It can connect to several data lakes and warehouses and fetches information like usage, lineage, table and column descriptions, no of queries, table level activities etc. It enables data lake warehouse usage analytics easy and user friendly. AI generated suggestions for deble and column description feature is also usful. Integration with communication tools like Slack save time to communicate and describe tables to users
What do you dislike about the product?
Sometime Atlan is bit slow to load all information about a data asset, which can deter users. Role based access mechanism is useful for user authorization, but sometime it is confusing if you have access to multiple roles.
What problems is the product solving and how is that benefiting you?
Previously it used to take a lot of time find usage details, lineage information, quality information about a data product. Now, Altan showcases all metadata information about all data assests in a central place. Its hugely time saving for data engineers, analysts, and data scientis to get information about the product. Data assets can be easily shared accross by integrated communication tools like Slack. Overall it plays a crucial role in the journey of data analytics democratization throughout the organization.
Best in Class Data Catalog
What do you like best about the product?
It is one of the best data catalogs in the market and I would say it has the best UX. It is easy to adopt and is designed to be close to where your users are looking at data (It has a plugin), which makes adoption a lot easier.
We are still rolling out all the features, but so far we have seen a lot of value, specially using the lineage functionality.
What do you dislike about the product?
It would be great if they had an easy way to add assets they have no connectors for. While the APIs are great, one of the reasons we selected them, there are tools where using engineering resources is too expensive or the tool we want to connect to does not have APIs. I understand we would not have all the features the API or the connector gives us, but it will not stop us from adding ALL data related reports in Atlan. Right now, we found a hack using Glossaries, but it would be ideal if they could make that available without hacks.
What problems is the product solving and how is that benefiting you?
It is making it easy for our users to discover our data assets and self-serve themselves at scale.
It is saving us a lot of time when we need to do an impact analysis e.g. what assets will be impacted downstream from making this change in our warehouse.
It is helping us streamline how we manage our data assets and making it the central place for all things data. Data consumers can submit tickets on a dashboard that has a bug or if they have an idea. It is a repository of all our knowledge around specific assets.
Best-in-class Active Metadata Management Tool
What do you like best about the product?
1. Atlan is deeply committed to innovation. Its products, such as Atlan AI and Atlan Mesh, are redefining the concept of an Active Metadata Management tool, also known as a data catalog.
2. The customer support and customer solutions teams at Atlan are highly engaged in helping clients achieve their goals. They often create custom packages or solutions to meet specific needs.
3. Atlan’s Chrome extension is noteworthy. It offers the convenience of an embedded Atlan solution within Databricks, Power BI, Google Chrome, and other platforms, eliminating the need to switch between applications. This seamless integration enhances user experience and productivity.
What do you dislike about the product?
While the product documentation is publicly available, some of it is outdated, which can sometimes lead to confusion among clients. Additionally, information about bugs and fixes is not readily available on the official website. Once a request is opened, it’s currently not possible to assign a priority level to it. This is an area that could benefit from improvement.
What problems is the product solving and how is that benefiting you?
Previously, Data Discovery was only available for a select few data and analytics roles. However, Atlan has provided the opportunity to leverage data quality from data assets through impact analysis and root cause analysis.
With Atlan’s workflow features, metadata and lineage curation have become possible. The tool also allows for the massive import of Business Metadata with custom packages and automation (playbooks).
Reporting analytics is another key feature of Atlan. It generates insights from tool usage, providing valuable data such as the number of weekly active users, the number of curated assets, assets with lineage, popularity, and more. This information can be instrumental in understanding user engagement and improving the overall user experience.
Atlan: A New Cornerstone In Our Data Management Journey
What do you like best about the product?
Atlan seamlessly integrated into our modern data stack, with Snowflake and Sigma at its core. The integration with Sigma, empowered by the Chrome Plug-in, emerged as a standout feature for us, elevating user experience and adoption. With the Chrome extension, all users in our BI enviornement have an enriched experience with Atlan providing data definitions and lineage while also enabling users to submit Jira tickets without leaving Sigma.
What do you dislike about the product?
The Atlan University is a great resource and training tool. However, the format of the short videos without seamless transitions could be improved.
What problems is the product solving and how is that benefiting you?
Our initial use case was finding a tool that could enhance our Data Governance strategies. However, when evaluating the product we found feature after feature that could either enhance user experiences, increase efficency, or identify cost optimization opportunities. Atlan quickly solved our Data Governance use case, but it also became a cornerstone for creating an enriched data enviorment through the creation of data glossaries, adding content and tags to objects via automated playbooks, and creating an opportunity to explore data and where it comes from through the lineage functions.
New Data Governance Strategy Easily Implemented with Great Platform
What do you like best about the product?
1.) Using lineage to conduct impact and root cause analyses to clean up our data. We were in the middle of a data re-architect before bringing in Atlan and now having it we can easily spot assets without queries or downstream attachments for clean-up and deprecation.
2.) Easy to use and intuitive UI, the browser extension is icing on the cake, end users can view information in Atlan without having to switch from their current screen to the platform, which is going to aid immensely in adoption. We've had users already solve issues using Atlan with little to no training.
3.) Customization features from personas and policies, to customizable messaging and scorecards to ensure integrity and accuracy the first time.
What do you dislike about the product?
1.) Some of the sublayers in licensing privileges are not clearly delineated and need to be specified at the persona level which could cause overages. A great example is insights licenses are not granted at the individual level.
2.) Atlan only goes to the tile level in Looker, it would be nice if they went all the way to the calculation for lineage and specificity without having to manually define it.
3.) The UI has basic spelling and grammar errors that could be cleaned up.
What problems is the product solving and how is that benefiting you?
- Curate sources of truth for data, document processes and definitions in one place, ensure relevance with periodic reminders.
- Implement standard communication processes.
- Mapping data from source to destination for root cause and impact analysis
- Permission and access governance
- Standardization across the tech stack
- Scorecards on metadata reporting to ensure maximum business ROI
Offers numerous out-of-the-box connectors, user-friendly interface and easy to manage
What is our primary use case?
Its core offering is a data catalog. However, it goes beyond that. We are building a hub of knowledge, encompassing business and data knowledge across the entire company.
The idea is that any employees or new hires needing onboarding can use it to understand the data they'll be working with, the data sources in the company, and the business knowledge of their field.
What is most valuable?
Atlan has many branches and features. Perhaps the most valuable one is the abundance of out-of-the-box connectors. As soon as you get access to the product, you can start using their connectors, which are easy to use and connect across a wide variety of data sources. This eliminates the need for lengthy development efforts to create new integrations.
They also offer automated lineage embedded in the connectors, allowing us to track where the data is coming from and where it's going. We find it very efficient in cataloging data sources.
Additionally, the user-friendly interface is a big plus, making it easy for users to familiarize themselves with the solution. These two features, in my opinion, stand out the most.
What needs improvement?
There are some improvements. There is a feature called Playbooks, which basically allows me to automate certain activities that would otherwise be manual. It's a very interesting feature, but there is room to improve it because, depending on the task you automate, the playbooks seem to have a hard time handling the task. So, it could be improved there. Even though it's a great feature, it can evolve further.
And the product as a whole Atlan could invest in features like a data marketplace. It would be interesting to have access to data because it is a data catalog, but it could also be the main marketplace where users request access to data to be able to define, and that access should be given in a seamless manner.
There is room for improvement on workflows as well, like the solution. It might not be the core of the solution, but they could start investing in having very robust workflows, especially for metadata data analysis. There is a simple workflow that could be improved.
For how long have I used the solution?
We have been using Atlan for seven months now since we started the partnership. But we began using Atlan for more than a year because we had a POC before.
So, we tested it a bit during the POC, finalized the partnership, and then began working with the tool in a productive environment, which is seven months now.
What do I think about the stability of the solution?
We haven't had many problems with stability. In terms of the connectors, for instance, we have been able to catalog more than a million assets, and we haven't had a lot of problems with the connectors or with retrieving the lineage of these assets.
However, playbooks might fall a little bit from this category. The playbooks are a feature of automated tests, and we see that depending on the test we want to automate, sometimes the playbooks have a little bit of trouble scaling. So, that's the only area of improvement in Atlan.
What do I think about the scalability of the solution?
We have almost 400 users. Among these users, we have business analysts, data analysts, data scientists, data engineers, architects, InfoSec, and information security officers. So, we have a very wide variety of professionals taking advantage of it.
How are customer service and support?
We had to reach out to customer service and support for a couple of reasons, maybe questions regarding the product, questions on how to use it in the future, but also with technical issues as well, like maybe a connector not working or the playbooks weren't working. And they were always available. They helped us solve our issues. So support is very good.
Which solution did I use previously and why did I switch?
We had a legacy platform. We worked outside the site with it, and that's why we decided to look at the market for a different solution, and that's how we found Atlan.
How was the initial setup?
It was fairly easy. The connectors are very easy to use. So, we just have to get user information into our environment, and we plug that user into the connector, and it's just gonna crawl all our assets for cataloging. The setup was very easy for us.
Also, because it's a SaaS solution, it's software. We don't have to set up infrastructure. We don't have to install it. It's just our website. We log in to our website, and we are good to go. So, a very easy setup, very easy to start using, and start delivering value.
The infrastructure of the solution is a fast solution for us. We're using the software and the user licenses. The infrastructure is from Atlan, and it's cloud-based, and it's on AWS.
What about the implementation team?
We have three people who look like admins. I am one of them. We have two others, and each one of us takes care of one aspect. I do overall management and work on expanding our scope of governance and, so, working on integrations with other data sources. I have colleagues who take care of day-to-day activities, keeping the environment updated, managing user permissions, and similar tasks. So, basically, three people.
What's my experience with pricing, setup cost, and licensing?
We pay per-user license. It's a different classification model than with other solutions, where they usually charge you for resources.
So, the more assets, the more data sources, the more processing you do, the more you pay.
Atlan only charges for users, and we established a model with them where we had a baseline of users. If we went past this baseline, we would pay proportionally to the number of users on the solution.
So, that was a better model for us. And because of this difference in models or classification, it was cheaper for us to go with Atlan.
Which other solutions did I evaluate?
We did look for other solutions. We actually had a period of work meetings with different vendors and did POCs with different vendors.
We compared a few open-source solutions as well and did a sort of checklist. We compared all the vendors in terms of which was a better match for us in terms of features, fulfilling our expectations, and costs—trying to figure out which of them made sense overall.
We looked into Informatica, Collibra, Big ID, MANTA, and OpenMetadata as open-source data lineage solutions.
What other advice do I have?
I would recommend using it because my experience with it has been very positive. To our strategy and our current maturity, it made a lot of sense, also within our budget. It was a very good cost/opportunity ratio, as other solutions were very expensive.
Overall, I would rate the solution a nine out of ten. Overall, it's a very good solution. It's a recent, brand-new, company-friendly solution. They have been able to fulfill our expectations.
We have been able to do what we wanted, to be where we wanted to be. They have a few issues here and there, but that's normal for any product or solution. Overall, we are satisfied.
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?
Amazon Web Services (AWS)
Nelnet: Active Metadata Solution Review
What do you like best about the product?
Intuituve UI, connectors align well with current data stack, and customer support engagement has been responsive and insightful. Product is well documented for our intended use.
What do you dislike about the product?
Playbook and readme template library would be an improvement.
What problems is the product solving and how is that benefiting you?
Atlan is being implemented as Nelnet’s active metadata platform to will help us maintain a more context rich line of sight into our environment, serve as both a technical and business metadata repository, and provide lineage from data source to reporting.
Industry leader in data cataloguing through active metadata.
What do you like best about the product?
1. Usability and UI really stands out
2. Alignment with the modern data stack and brilliant integartions with tools like Snowflake
3. Support team with a wealth of knowledge
4. A Wealth of capabilities and features with customisation through playbooks which is really helpful for things like classification tags.
5. Out of the box reporting with customisation
6. Speed to delivery, innstance was setup in less than 48 hours
7. AI and Machine learning capabilities for automation curation, speeds up defitions anf approvals
What do you dislike about the product?
Some improvement areas would be:
1. Improvements to integartions with Excel which is coming soon.
2. Customisable profiling rule, OOTB capabilities dont allow you to customise profiles, although this can be worked around through querying.
3. More customisation with reporting
What problems is the product solving and how is that benefiting you?
We are building Atlan as the single UI for all of our data users, proving transparancy in how data is curates, calculated and owned. Speeding up delivery through self service for our global analysts and supporting our efforts in validating our data estate
Give your data governance initiative a jump start with Atlan!
What do you like best about the product?
1. Rich data lineage with easy setup and readability
2. Automation capabilities to propagate data tags are user intuitive and easy to configure
3. User interface is consistent and easy to navigate
What do you dislike about the product?
1. Submitting issues and enhancements is easy but often results in limited insight into the path to resolution from the support team
2. Out of the box reporting capabilities exist but have a significant opportunity for improvement
3. Data profiling feature as it is provides little to no value and would be extremely beneficial if customer feedback was incorporated into the offering
What problems is the product solving and how is that benefiting you?
Altan is helping us solve the need for a scablable platform that enables active data governance and supports our data stewards. The concept of playbooks is fantastic and allows you to classify your data assets through automation at scale.
