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)
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.
Next generation data cataloging, discovery and governance
What do you like best about the product?
Atlan's integration capabilities have impressed our data engineering team, providing a seamless setup experience.
The user experience (UI) of Atlan deserves special mention. Its intuitive interface simplifies navigation and usage, making it a powerful tool for metadata management.
Additionally, the considerable engagement demonstrated by the Atlan Account Executive and Engineer contributed to a seamless tool evaluation process. The Customer Success Management program played a crucial role in effectively planning and executing the rollout process.
What do you dislike about the product?
Depending on a company's maturity level, the multitude of features provided by Atlan can be overwhelming. While these features hold significant potential, their abundance might prove to be overpowering for new users, potentially hindering their ability to fully leverage Atlan's capabilities.
What problems is the product solving and how is that benefiting you?
Atlan helps to address a range of data management challenges:
1. Search and Discoverability: Atlan's robust features enable effortless search and discovery of data assets. This enhanced accessibility facilitates data-driven decision-making.
2. Data Lineage: Atlan's capabilities in providing data lineage offer a comprehensive view of data journeys, contributing to better understanding and analysis.
3. Ownership, Governance, and Access Management: Atlan's features ensure clear ownership and governance of data assets.
4. Reducing Dependency on Data Personnel: By serving as a comprehensive repository of information about data assets, Atlan results in improved work efficiency and accessible data-related context.
A great product, with even better potential.
What do you like best about the product?
What I appreciate most about Atlan is its emphasis on collaboration and automation. Its ability for data discussions and annotations make it a truly collaborative platform, stimulating efficient dialogue among data teams. This increased level of collaboration often leads to enhanced data understanding and more insightful decision-making.
The platform's automation also plays a significant role in its appeal. In just a few clicks, we can automate repetitive tasks, allowing us to focus our time and energy on providing insights rather than wrestling with tedious data management tasks.
Combined with its robust data governance capabilities and comprehensive audit trails, Atlan simplifies data oversight and assists in staying compliant with data protection regulations. Overall, Atlan's dedication to fostering an easy, collaborative, and compliant data environment is what I find most compelling.
What do you dislike about the product?
Despite its myriad of features, Atlan has one significant setback that can affect new users most: its onboarding process. Getting up to speed with Atlan's tools and functionalities can be quite challenging due to the steep initial learning curve. This might be attributed to its wealth of features and capabilities which, while beneficial in the long run, can overwhelm users.
What problems is the product solving and how is that benefiting you?
Atlan has been instrumental in addressing several critical data management issues in our workflow. To begin with, as an organization with colossal volumes of data to work with, finding the right data when needed used to be like looking for a needle in a haystack. Thanks to Atlan's data catalog and discovery capabilities, we've managed to centralize our data resources, making it much easier to access and discover the right data when we need it.
When it comes to team collaboration, Atlan has been great. Before using Atlan, collaboration on data projects used to be complicated, lengthy, and prone to miscommunication. With Atlan's rich-sharing and collaborative features, all members of the team can collaborate on shared data assets, add their input, and make decisions collectively in real-time, leading to more cohesive collaboration and decision-making.
Data governance and compliance is another critical area where Atlan has proven invaluable. Atlan's automated compliance checks and comprehensive audit trails have made maintaining compliance a much more effortless process. This feature not only minimizes risks but also offers peace of mind, knowing that we are handling data ethically and responsibly.
In essence, Atlan has played a pivotal role in streamlining our data processes, promoting data democratization, ensuring compliance, and fostering better collaboration within our data teams.
Atlan has been a powerful tool for me as a Product Manager
What do you like best about the product?
'Build query' feature is a great tool for people without expertise SQL and is also a great way to learn more about how to build SQL queries.
What do you dislike about the product?
No way to easily import csv files to include in Join functions or in build query feature.
What problems is the product solving and how is that benefiting you?
Ease of access to tables across our data lake. Ease of joining data across our data lake.
Data Cataloging Simplicity
What do you like best about the product?
Atlan is great for our data stakeholders to be able to easily find data in our data lake. There is data that some stakeholders didn't know existed. In addition, their Insights feature makes it very easy for someone with limited SQL experience to query data.
What do you dislike about the product?
One of the downsides is a feature that we haven't been able to use yet. They have the ability to create data lineage from your metadata. Unfortunately, our data is stored in Athena which isn't currently supported.
What problems is the product solving and how is that benefiting you?
We used to keep our data dictionaries in an Excel spreadsheet and our data engineers had to make modifications to the sheet every time a table was modified. With the introduction of Atlan, our stakeholders were able to access the data and we were able to have it automatically update the metadata when tables were modified. This meant our data engineers could focus on creating new pipelines and doing the transformations we needed. It increased productivity because the data support questions could often be answered by Atlan.
Amazing Resource for Data Dictionary
What do you like best about the product?
Atlan has decreased the time it takes to research our internal data sources and the relationships data within our warehouses. As a data engineer, it's also alleviated our team of being the single source of knowledge for the definitions of our data.
What do you dislike about the product?
There's a query option within Atlan that I don't have much use for. The data preview is extremely useful, but any sort of query development is much better served or accomplished with another tool that we have because those other tools are more robust.
What problems is the product solving and how is that benefiting you?
When I look at data within our data warehouse, I sometimes do not know the definitions of specific metrics or the source. The data dictionary within Atlan forces us as engineers to take the design thinking we used to build pipelines, data tables, views, etc and define it for the larger organization. It also supports historical data understanding and architecture to make decisions for new products that we engineer for our stakeholders. Atlan provides the means for us to investigate, design and define the data that we are ingesting and use on a daily basis.
Atlan as the ideal interactive business metric catalog product
What do you like best about the product?
Atlan provides not only a robust product for metadata management, but also a great customer experience in terms of both UI as well as implementation support.
I especially liked the seamless integration with our data assets hosted in BigQuery and Looker.
Our Customer Success Manager and his team were extremely helpful during the rollout and provided various practical advice on how to engage the relevant teams in my company.
What do you dislike about the product?
As the product is complex and dynamic (improvements keep on coming), there were a few cases where it did not work perfectly. Fortunately, all operational issues were rather quickly (hours-days) resolved by the helpful support team.
What problems is the product solving and how is that benefiting you?
The main use case for us is the introduction of a single source of truth for business metric definition, including live links to our data assets (DB & BI tools) and additional information about the business metrics (ownership, description, links to other documentation etc.)
Atlan G2 Review
What do you like best about the product?
The ease of use for creating glossaries, terms, tags & certs is awesome. It doesn't take a lot of clicks to find information and to relate data to specific topics.
What do you dislike about the product?
At the moment, the "welcome" page is not customizable. It would be great if we were able to customize this to how our company communicates
What problems is the product solving and how is that benefiting you?
We currently have information about data in several places (confluence, jira, slack, google apps, etc) by allowing the original documents to be linked from their places of origin onto the data assets; this gives freedom to continue to update the original documents but also provide a one-stop source to all related information.
