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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.
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.
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.
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.
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
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
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
Great experience! The simplicity allows for a great user experience.
What do you like best about the product?
The search option for looking up data sources/fields is beneficial. I believe this is the most used resource due to the data in our databases. The ability to add definitions to the fields ensures the correct data source is selected.
What do you dislike about the product?
Atlan has a lot to offer, but knowing what all Atlan can be used for is challenging.
What problems is the product solving and how is that benefiting you?
Atlan solves the issues of locating data tables and fields. The search ability helps users find the proper data source to complete their job functions without depending on a specific team to point them to the correct source.
Modern Catalog with E2E Visibility
What do you like best about the product?
Atlan has built-in first party integrations with Snowflake, PowerBI, Sigma, Fivetran, and dbt.
Instead of relying on engineering teams to spend months at a time to integrate to Atlan, we can get quickly up and running in weeks, if not days.
Atlan has one of the strongest data lineage parsing mechanisms out there that creates a comprehensive data lineage view of data assets from Snowflake database tables / views to the models that transform them, and even exposes through to PowerBI.
The interface is easy to use and bridges the gap between technical metadata and business contexts of datasets with the glossary of the organization.
Its true strength is enabling a single collaboration area between engineers, analysts, and business users alike to empower organizations to become data centric.
Instead of relying on engineering teams to spend months at a time to integrate to Atlan, we can get quickly up and running in weeks, if not days.
Atlan has one of the strongest data lineage parsing mechanisms out there that creates a comprehensive data lineage view of data assets from Snowflake database tables / views to the models that transform them, and even exposes through to PowerBI.
The interface is easy to use and bridges the gap between technical metadata and business contexts of datasets with the glossary of the organization.
Its true strength is enabling a single collaboration area between engineers, analysts, and business users alike to empower organizations to become data centric.
What do you dislike about the product?
Although Atlan is expanding into various integrations across the ecosystem, there needs to be a way to accelerate the first party integrations to other strong ecosystem partners like Coalesce and Soda.
What problems is the product solving and how is that benefiting you?
In our organization, our analysts and engineers are spending an outsized amount of time answering questions about data.
This is due to a combination of different factors where ultimately, we lack the ability to have visbility and transparency across the data assets in our organization.
Atlan will be solving this by providing a holistic view of our datasets from source to reports that will then empower our business users to self service their own questions across data.
This is due to a combination of different factors where ultimately, we lack the ability to have visbility and transparency across the data assets in our organization.
Atlan will be solving this by providing a holistic view of our datasets from source to reports that will then empower our business users to self service their own questions across data.
Next Generation Data Governance
What do you like best about the product?
Clean, user friendly interface. Was relatively painless to get all of our data sources added in quickly and we had all of our sources supported right out of the box. Beyond the obvious usefulness of end to end lineage, that mining features are also great for understanding what tables and columns are most used, and even helps identifying slow or expensive queries. Chrome extension allows users to get to information without switching applications and Teams integration helps keep questions centralized and front of mind for the org. Support and Customer Success have been great to work with. Upcoming AI features will make managing the platform with minimal staff even easier, and should also help drive user adoption through ease of use.
What do you dislike about the product?
One function I would like to see added is the ability as an admin to see the application as a particular user does. With personas and purposes you can deeply customize what a user can see and do and having the ability to quick validate that instead of needing test accounts would be a timesaver.
Additionally the text editing in the Glossary is extremely basic and needs simple functions like Undo added.
Additionally the text editing in the Glossary is extremely basic and needs simple functions like Undo added.
What problems is the product solving and how is that benefiting you?
Atlan is making it easier for business users to understand exactly how metrics are being calculated, where that data is coming from, and if there are any known issues with it. Combination of the data lineage and glossary removes all of the mystery behind where numbers are coming from and will increase confidence in the accuracy of what they are seeing. This also frees up the data team to focus on future enhancements instead of spending so much time answering questions and chasing down issues.
Fantastic Data Catalog for Data Operations centric organizations
What do you like best about the product?
Atlan's ease of use and configuration certainly helped us get started quickly and make an impact to our data ops-heavy organizations.
What do you dislike about the product?
There are some minor quirks to the UI, but the support team are interested in all user feedback and have made changes quick based on our input.
What problems is the product solving and how is that benefiting you?
Centralized data discovery and governance
Incredible tool for data-curious users
What do you like best about the product?
I love how easy it is to get access to find the answers I need using SQL. Before Atlan, I would have needed to jump through many loops to access our data. With Atlan, I can access all tables, which are organized and described clearly so that I can discover data efficiently. Atlan also makes crafting, saving, sharing, managing, and reusing SQL queries simple.
What do you dislike about the product?
Nothing - even when I have had issues in the past, Atlan's team would work to resolve them quickly.
What problems is the product solving and how is that benefiting you?
Atlan helps teams answer questions quickly. They provide the tools needed to get into your data and come out with a clearer understanding of what you need to be answered. They make this process as seamless as possible, ensuring the user can focus on the decisions they need to make instead of messing with data.
Streamline the Metadata Management: Unlocking Efficiency and Accuracy
What do you like best about the product?
I'm responsible for building up the glossary in Atlan - the reason why we believe Atlan is a user-friendly and collaborative metadata management platform and is the perfect fit for building up our glossaries are below:
1. Definitive definitions: 1) The glossary allows users to define and document business terms and metrics, providing clear and consistent definitions to ensure a shared understanding. 2) The glossary provides contextual information, including synonyms, abbreviations, acronyms, and related terms. 3) Terms and metrics can be categorized and organized in a hierarchical structure, facilitating easy navigation and browsing based on domains, topics, or functional areas.
2. Search and Discovery: The glossary offers powerful search capabilities, enabling users to quickly find specific metrics or related information. Users can search by keyword, browse categories, ownership, or apply filters to refine their search results.
3. Data Lineage and Impact Analysis: The glossary is integrated with data lineage and impact analysis features. Users can understand how terms are used within reports, dashboards and other data assets, and trace their impact across the data ecosystem.
4. Collaboration and Annotation: Users can collaborate by adding comments, annotations, or additional context to term definitions. This encourages knowledge sharing, discussions, and alignment on the understanding of terms.
1. Definitive definitions: 1) The glossary allows users to define and document business terms and metrics, providing clear and consistent definitions to ensure a shared understanding. 2) The glossary provides contextual information, including synonyms, abbreviations, acronyms, and related terms. 3) Terms and metrics can be categorized and organized in a hierarchical structure, facilitating easy navigation and browsing based on domains, topics, or functional areas.
2. Search and Discovery: The glossary offers powerful search capabilities, enabling users to quickly find specific metrics or related information. Users can search by keyword, browse categories, ownership, or apply filters to refine their search results.
3. Data Lineage and Impact Analysis: The glossary is integrated with data lineage and impact analysis features. Users can understand how terms are used within reports, dashboards and other data assets, and trace their impact across the data ecosystem.
4. Collaboration and Annotation: Users can collaborate by adding comments, annotations, or additional context to term definitions. This encourages knowledge sharing, discussions, and alignment on the understanding of terms.
What do you dislike about the product?
1) Pricing: Atlan's pricing structure may not be suitable for low budget companies, especially for small organizations or startups with limited resources. Will enterprise pricing plan in the pipeline?
2) Learning Curve: It might take some time for users to become proficient in navigating and utilizing all the functionalities effectively.
2) Learning Curve: It might take some time for users to become proficient in navigating and utilizing all the functionalities effectively.
What problems is the product solving and how is that benefiting you?
During our implementation of the Notion glossary, we gained valuable insights and underwent a significant learning experience. However, we encountered a set of challenges that have led us to make the decision of transitioning to a more suitable tool capable of effectively serving the entire organization. Below are the key learnings we derived from this process:
1. Inadequate understanding and communication
In many cases, there is a lack of sufficient understanding regarding critical topics, particularly when it involves metrics that are defined differently across various teams. Let's consider the example of DIFM. Due to breakdowns in communication, aligning the calculations for different perspectives of net revenue took considerable time and effort.
1. Operational complexity
Given the unique nature of our business, certain metrics can be challenging to grasp, such as revenue recognition at different points in time. Additionally, there may be high entry barriers for one department to understand the metrics used by another department. Moreover, when our business model undergoes changes, there tends to be a multitude of news and updates that colleagues outside the core team or channel might not be aware of, resulting in a lack of context.
1. Lack of ownership
Colleagues often express a desire to learn more about specific metrics, but struggle to identify the appropriate team or location to access the relevant information. Complicating matters further, the search experience in Notion is suboptimal. For instance, when using a table (database), users are required to load the entire table to perform a search or add filters to narrow down their search. This limits the efficiency and ease of finding the desired metrics and related information.
1. Inadequate understanding and communication
In many cases, there is a lack of sufficient understanding regarding critical topics, particularly when it involves metrics that are defined differently across various teams. Let's consider the example of DIFM. Due to breakdowns in communication, aligning the calculations for different perspectives of net revenue took considerable time and effort.
1. Operational complexity
Given the unique nature of our business, certain metrics can be challenging to grasp, such as revenue recognition at different points in time. Additionally, there may be high entry barriers for one department to understand the metrics used by another department. Moreover, when our business model undergoes changes, there tends to be a multitude of news and updates that colleagues outside the core team or channel might not be aware of, resulting in a lack of context.
1. Lack of ownership
Colleagues often express a desire to learn more about specific metrics, but struggle to identify the appropriate team or location to access the relevant information. Complicating matters further, the search experience in Notion is suboptimal. For instance, when using a table (database), users are required to load the entire table to perform a search or add filters to narrow down their search. This limits the efficiency and ease of finding the desired metrics and related information.
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