Alation Data Catalog Reviews

My main use case for Alation Data Catalog is data discoverability and metadata management.

In my day-to-day work, I use Alation Data Catalog for data discoverability and metadata management by ingesting metadata from a number of different data platforms, including Snowflake and Power BI. We use the lineage features to keep track of where the data is moving within our environment. We also maintain certain items related to our data assets, including sensitivity tags and data descriptions, which makes it easier for our self-service analytics users to find the data they need.

The best features that Alation Data Catalog offers are its search capabilities and the fact that it works with many different data platforms; it is essentially platform agnostic. The other piece that I really think is important is how easy it is to use as well as to manage.

What makes the search capabilities of Alation Data Catalog stand out for me is the fact that every item within the catalog is indexed and searchable, as well as the filtering features that allow you to narrow down to just the types of assets that you need. Wildcard searches are also very helpful. It is a very intuitive tool, as long as you are using the filters.

Alation Data Catalog has positively impacted my organization by allowing users to answer questions that they had without trying to track down an expert. This has saved them quite a bit of time and frustration. It has allowed them to solve problems they probably would not have been able to solve had they not had the catalog.

We have been measuring the curation of content within the catalog that has gone up over time, and we have also seen the number of users in the catalog increase, as well as the amount of activity within the catalog increase. We were seeing about an average of about 20% increase month over month for the last few months.

Alation Data Catalog can be improved by enhancing their lineage capabilities to make it easier for us as users to search the lineage without having to use the Alation Data Catalog user interface. If they could put it in a relational format, then we could join that information with other metadata from other platforms. We could join it in reporting. Lineage improvement would be the biggest thing.

I have been using Alation Data Catalog for eight years.

I choose a nine for my rating because it has been extremely easy to use and extremely easy to set up. It allows us to automate our curation. It allows us to integrate with metadata from other platforms, such as Power BI and Snowflake. It gives us a much better overall view of our data environment. The search capabilities are extremely useful. It is easy for a user to come in and find what they need without having to learn a very complicated tool.

My advice to others looking into using Alation Data Catalog is to give a very close look at the capabilities and make sure that they suit what your organization needs. If you are looking for better data discoverability, Alation Data Catalog is basically your best choice. Consider which connectors that you want to purchase, since those are licensed separately. Make sure that you purchase only what you need as far as that goes. Consider trying to integrate Alation Data Catalog information with other platforms as well to allow you to improve upon reporting. That worked successfully for us. I give Alation Data Catalog a rating of nine.

My main use case for Alation Data Catalog is that we have been working on a cyber data lake program that deals with a lot of data governance and cataloging, which includes cybersecurity data, patient scan data, PDX data, as well as lots of data from the regulatory board.

Regarding how I am leveraging Alation Data Catalog, there are many scopes that we are now exploring where the catalog can be expanded with other use cases, which deal with the financial aspects of healthcare that can be implemented in customer engagements as well as vendor engagements that we have on a day-to-day basis. By utilizing AI in this robust space, cataloging all this information in this AI era helps a lot because the data is enormous, and as a medtech company, we need to ensure that none of the data we maintain is brought outside of the catalog and is maintained robustly.

A specific example of how Alation Data Catalog helps with cybersecurity or patient scan data is that we have been able to establish a lot of data lineages, including how the data gets changed over the period of time. When it comes to regulatory compliance, it helps a lot in terms of the cataloging, balancing this data such as PII and HIPAA compliance-related information, and it is not just about the catalog; it is about how we maintain the data from an accessibility point of view, who is responsible for managing this kind of data, and it prevents data loss. From a cybersecurity perspective, using the catalog, we have been able to implement rule-based DLPs and DLP policies.

The best features Alation Data Catalog offers include how it provides labels, understands which data catalog or areas we have dealt with related to lineage, finding relations, and discovering usable data. It ensures that the data catalog is primarily built on core principles such as stewardship, quality, and master data management. I really appreciate the way Alation provides support in maintaining our features.

The stewardship and master data management features specifically help my team by linking KPIs to business outcomes and continuously tracking performance. We are able to set up a business glossary with business names, definitions, descriptions, ownerships, and related undocumented insights of contextual knowledge. This includes medical transcription points of view and customer test analysis, allowing us to automate repetitive workflows and identify manual workflows to automate using the data catalog. From an audit perspective, we also do business adoptions, maturity and culture assessments using surveys and collaborative techniques.

We are able to build controls by designing procedures and policies that define how people and systems will use the data, especially for data moving internally and externally. One crucial element from a data management point of view is controlling vendor access, given that we engage many vendors. Using principles of least privilege for vendor access should be our first case. Once these controls are established, we create systems that audit and test their effectiveness. We are also using five components of the data governance model, providing clear notices regarding data governance policies, forming a data governance panel, establishing controls, and setting up a data inventory for performance and due diligence.

Alation Data Catalog has positively impacted my organization by helping us establish data governance and privacy. For functional strategies, we identify data systems and individuals that need to be included in our security strategy using the catalog. It improves the protection of systems that hold our data, detecting attacks at earlier stages in the life cycle and responding to those attacks in ways that support both data security and governance systems. We have improved data quality and accuracy, made informed decisions faster while reducing risks, and ensured compliance by enabling security and efficient access. Importantly, we establish a single source of truth, centralizing metadata and standardizing definitions, which minimizes confusion and helps with consistent data use across the organization.

We have seen a lot of ROIs in areas such as improved data access features enabled through the catalog, ensuring that the data end users and downstream applications access does not have breaches. Now that we have established clear governance policies, assigning the right access to the right users helps teams work independently while reducing reliance on subject matter experts. From a risk and compliance perspective, adhering to HIPAA, PCI, and PCI DSS standards helps protect sensitive data from misuse or breaches.

Alation Data Catalog can be improved by treating areas that could incorporate best practices or improvements, such as identifying data domains, which refer to logical data groups customers, vendors, and other entities. Another area for improvement is determining the most important elements of data and deciding between adopting a centralized or decentralized operating model. These decisions could come in advisory forms sent by the system, helping establish metrics for measuring our success. Additionally, bringing in AI capabilities to automate tracking and labeling can optimize how we handle data information levels.

Regarding improvements, establishing success metrics such as concrete numerical benchmarks for our data governance policy would be helpful goals. For example, measuring the average time it takes someone to access the data needed for their job would be an important feature to improve.

I have been using Alation Data Catalog for more than six years.

Alation Data Catalog is absolutely stable.

The scalability of Alation Data Catalog is remarkable; as data sizes grow, we can also scale categorizations, calibrations, and the types of data we ingest and catalog through this tool, which has been a strong asset for us.

Customer support for Alation Data Catalog has been great; we have defined several SLAs that have resolved critical issues and incidents with excellent support.

Positive

Before using Alation Data Catalog, we had several on-premise legacy systems, which we phased out over the last four to five years in favor of Alation Data Catalog.

We have seen a return on investment, having saved close to 10.5% of our costs, with expected ROI growing yearly by about 17%. We saved over 1,000 man-hours in a single year, which was crucial.

My experience with pricing, setup cost, and licensing for Alation Data Catalog is positive; discussions with the vendor partners provided a detailed breakdown of costs and how they can be reduced over time, which was a great experience.

Before choosing Alation Data Catalog, we evaluated numerous options that went through a rigorous selection process.

My advice for others looking into using Alation Data Catalog is to start using this tool if you want to manage cataloging, data governance, compliance, and risk-based metrics. It has been an amazing asset for us in managing complex use cases related to data management. I believe we had a good discussion, and I have provided a lot of information. I would say keep updating features, continuously adding more AI, and help us on that journey. I would rate this product and experience a nine out of ten.

I am the administrator and server admin for Alation Data Catalog. We create custom processes to upload metadata into Alation Data Catalog. We are trying to get as much metadata into Alation Data Catalog as possible and integrate it with other tools that we are also building. The main purpose of Alation Data Catalog at Upstart is to help people looking for data find the data they need and how to use that data.

Recently, many people are trying to deprecate tables in the source databases and find what downstream impacts that would have. They use Alation Data Catalog lineage to determine if there are any obvious uses of these tables. This is the biggest use case recently. People also use it to find descriptions and service owners.

I use Alation Data Catalog's analytics piece, Alation Analytics, to create dashboards in Databricks based on annotations or source comments on the databases themselves. This allows us to hold teams who own these tables accountable for missing annotations or possibly incorrect annotations on the source databases.

The best feature that we have used the most in Alation Data Catalog is the lineage and impact analysis piece. This is used in other services where we call Alation Data Catalog API to get the lineage and then use that as input to some LLM models and other services that another team builds for lineage services. We use the API extensively, and it is a great piece to get context. It is great to have all the context in one place, and we can use inputs to LLMs to chat with data when we create our own solutions, since Alation Data Catalog does not offer the exact answer we want for our custom LLMs yet. We are creating that as context input, and we are able to see descriptions, types of columns, and search easily, even though the search can be a little inconsistent sometimes.

Alation Data Catalog's scalability has met our needs as our data and user base has grown. We mostly need viewer access, so the licensing with the cloud-native solution allows unlimited viewer access. There are no other limits that we have even found except some of the API limits on the free version where we would have to pay if we wanted to increase our API calls.

Alation Data Catalog API integration has mostly been smooth. We have seen issues with the LLM API pieces or lineage, but there is not clarity around what the costs are, how many requests exist, and what constitutes a request to this API. One issue that we found before, which I believe is solved now, is using the same refresh token in multiple different processes that could run in parallel. The refresh token would create an API token, and the API token would then get invalidated if another process uses the same refresh token to create an API token. We are now starting to use service accounts by Alation Data Catalog and will have different service accounts for each process, so this does not happen anymore.

The current search functionality in Alation Data Catalog is not necessarily great. It does not do natural language searching as we would prefer. It mostly searches titles, and we would prefer it to search the description and some of the source comments to find answers that we need. Additionally, we would like to be able to search common queries or the queries that are used most frequently for certain aspects so people can get ideas of what queries they can use when they want to find a specific metric.

We have been able to find downstream impacts easier with Alation Data Catalog. Our machine learning team uses it quite often to find certain data. Our analytics team has yet to adopt it as much as we would prefer because it does not have the easy finding features for searching and finding queries that they can use or endorsed queries. They want to figure out how to use the tables and join them to find other metrics, which is difficult in the current state, though I believe there are things in the future to improve on. The other aspect is holding data producers accountable and being able to see who owns tables. Currently, that is a manual process, but we are creating an automated process to add owners to tables. If anybody has a question on a table that the description may not have answered, then we can find that out through the owner of the data in Alation Data Catalog table page.

We do not have as many P1 incidents anymore based on anecdotal evidence. Previously, a change may have happened and people did not know about the downstream impacts, which caused a lot of issues. Now it is easier to mitigate or just not encounter the P1 incidents in the first place.

The search feature of Alation Data Catalog could be improved. Alation Data Catalog Compose is also interesting in that we cannot search queries or see queries in the table page that are not published unless we go to the query history. We do not allow Compose on many items right now due to information security. Our security requirements do not allow Alation Data Catalog to access the underlying connections because we do not want people to pull in data. From a security standpoint, that is an issue, and we would like to have workarounds in certain cases. The other issue that we have found recently is along the same lines of security. We do not want to automatically sample tables in Alation Data Catalog because there could be some issue or we do not want that data being stored on a different server. However, if we have a schema that is enabled for sampling, then any new table automatically gets enabled for sampling. We have had to work around this by trying to figure out the correct permission and setup on the Databricks side to not allow Alation Data Catalog to sample certain tables if we do not want it to, because it is not feasible to do that on Alation Data Catalog side.

I have been using Alation Data Catalog for over a year at this point.

Alation Data Catalog is stable for the most part. There are some issues with long load times for DBT models, but for the most part, it is stable. It has never gone down when we wanted to access it.

Alation Data Catalog's scalability has met our needs as our data and user base has grown. We mostly need viewer access, so the licensing with the cloud-native solution allows unlimited viewer access. There are no other limits that we have even found except some of the API limits on the free version where we would have to pay if we wanted to increase our API calls.

We do interact with customer support for Alation Data Catalog quite often for certain issues like missing Looker lineage in some Redshift tables. The support time can vary. If the issue is well known, it is usually quick or easy to figure out. On the more complex issues like missing lineage, those took much longer than we would prefer because the engineering team has to get involved. Some of them have dragged on for six months, which is much longer than we would ever want some support issues to go on.

Positive

We do see a return on investment, though I cannot share exact numbers. There are fewer questions being asked in our ask data platform channel or some other channel about data itself since the implementation of Alation Data Catalog.

My advice for others looking into using Alation Data Catalog is to use the cloud-native solution. Using on-premises is much more difficult to deal with, and it is much more time-saving to use Alation Data Catalog cloud service provided by Alation so you do not have to deal with most of the things. Make sure that the security requirements are met if you want to pull in data. Ensure that your security best practices allow that and there is no sensitive information that could potentially get leaked into Alation Data Catalog causing you to have to ask Alation Data Catalog to delete that data, which can take some time. I would rate this product a 7 overall.

My main use case for Alation Data Catalog is for data governance and for non-tech business users who especially want to understand some tech terms. For example, we have a huge data warehouse where every field in each database, in that particular table, in that particular schema, needs to be explained, and we try to streamline that technicality in a user-friendly non-technical way. That is where we use Alation Data Catalog to do the data governance and to provide information to non-technical business users.

Majorly, we do data governance and help business users, including non-tech business users, and this is the main use case for us.

My advice for others looking into using Alation Data Catalog is that it is a great tool, as it can help non-business users, has a robust business glossary, and aids in making faster, strategic decisions while improving productivity. I would highly advise others to use this tool as a data governance tool.

I appreciate the features in Alation Data Catalog, including data quality, faster data discovery, data stewardship, privacy choices, tracking data usage, collaboration, data governance, and open connected frameworks. Data stewardship is something I really use a lot, as it describes the activity associated with curating and governing data so that other users can find, understand, trust, or use it. A good data catalog should empower data leaders to identify data stewards based on the work already done, assign relevant assets to stewards, and clearly define responsibilities for them, fostering accountability and ensuring that the data is correctly handled throughout its lifecycle.

When it comes to data stewardship, Alation Data Catalog makes my job easier by providing a robust business glossary, which is another key tool for stewardship leadership to seek in a data catalog. It serves as a central repository that lays out a clear data-backed definition of terms, such as profit, with business metrics to ensure clear, consistent communication across departments. The stewardship capability I use majorly is a robust business glossary, which I wrote and managed.

Alation Data Catalog positively impacts my organization by improving data efficiency, data quality, and collaboration. My stakeholders can find relevant data assets quickly using a Google search without needing technical jargon, reducing the time spent searching for data. It has also increased productivity by streamlining data discovery and providing context, allowing analysts to spend more time on analysis instead of searching and preparing, so they can just start their analysis. Business users are empowered to access and understand data independently without relying on IT teams or developers for ad-hoc requests. For example, even my product owner does not usually go directly to the data engineer or developer with any doubt; she can search in Alation and understand the business glossary in a user-friendly manner. Additionally, when a new analyst or new member is onboarded, it helps them to understand things more quickly thanks to the centralized documentation in the catalog or business glossary.

Regarding improvements for Alation Data Catalog, I mention pain points, but I find it difficult to identify any. I do not have any pain points with Alation Data Catalog as of now; I could not think of anything that needs improvement.

I have used Alation Data Catalog for 1.5 years, and I closely work with the product owner who is the product owner of Pizza Hut Global, where we do some data governance and data steward work, which is where I use Alation Data Catalog.

In my experience, Alation Data Catalog is stable, as I have not encountered any downtime or reliability issues.

Alation Data Catalog handles growth and increased data volume well for my organization, as it has good scalability.

I have not needed to contact customer support for Alation Data Catalog, so I have not faced any issues with customer support, and everything is sorted for our team.

Positive

I did not previously use a different solution for data governance or cataloging before Alation Data Catalog.

I think we are just consumers of the service from Alation and not in a business relationship as a partner or reseller.

I can share that when I joined, Alation Data Catalog helped me to understand things and reduce my time, cutting it by 50 percent. Instead of going into Google or consulting a colleague, I can just go to Alation Data Catalog, search there, and understand everything by myself. Thus, it reduced my time and saved my colleagues' time, so I can say at least 50 percent of my time is saved.

I do not have any insight on the pricing, setup cost, or licensing, as those matters are handled by the finance team, so I cannot comment much on it.

I am not certain of other Alation Data Catalog solutions since my company was already using it when we started.

Alation Data Catalog is deployed in our organization on a cloud. We use both Azure and Google Cloud for Alation Data Catalog. Alation Data Catalog leads to faster decision making, as it helps in providing a single simplified view of data and clear definitions, allowing teams to find and use the right data more quickly, leading to better-informed and faster strategic decisions. I would say faster decision making is a key benefit. I would rate this review overall as a 10.

As one of the data champions, I have been curating the data that I work with closely, and I also use Alation Data Catalog to look up data tables and fields that I are unfamiliar with but have been asked to provide analytics for.

For example, I was asked to provide an analysis of the NAICS codes and how they're being used, what loans are what NAICS codes at our bank, so I had to go and figure out what NAICS codes were and where what table it would be in because I didn't know. Instead of going to another analyst, I was able to look for myself and save some time.

We also use Alation Data Catalog to curate information about the Power BI dashboards that we have, so that way analysts know what's already available and they don't have to recreate the wheel. This has saved me a couple of times from having to create an all-new dashboard for a quick request that my manager asked for, allowing me to see what the other analysts have been working on, which has helped us be a lot less siloed in our bank.

The best feature of Alation Data Catalog is probably being able to search and see who owns what data, including who's the person that's curated it and who's the data champion for it because I often have questions that go along with it, so it's really helpful to know who owns what data.

Being able to look up a data field in a data table and know who owned that data has helped me a lot in my day-to-day work, as I've been able to ask them questions about their dashboard. I've had somebody add one thing to their dashboard that helped my team before. I also needed to ask data questions so that I can finish any metrics that I'm working on or creating, so that's been really helpful.

Alation Data Catalog has positively impacted my organization as collaboration has definitely improved at my company. We've been able to reach out and know who owns data, especially because sometimes there's turnover or new faces, and we're constantly building out the analytics side of our bank. It's been really great to meet other analysts and get our jobs done effectively, especially since I'm in second line and it's hard to have more than surface-level knowledge of the data. It's been great to reach out to those subject matter experts and other analysts.

Sometimes the search function in Alation Data Catalog isn't as effective as it could be. I've had times where I wish that the search engine or the search bar would find something even when I know that it is a field that's available, but it won't. I still have to go and ask someone where it is, so I think the search function could use some improvement.

The biggest improvement I could think of for Alation would be to enhance the efficiency or effectiveness of the search engine, or have it perform better at searching for keywords that are within the data field name or the table, particularly what fields are in the table.

I chose an 8 out of 10 mainly because of that search function. The auto-naming function doesn't seem to learn as quickly, and that's another improvement. Sometimes it doesn't train past a certain point when it comes to tables that I am the champion of with similar names, and I wish it would pick up on the context of the table name and the data field name.

I've been using Alation Data Catalog for two to two and a half years now, and I'm one of the data champions at my bank.

Alation Data Catalog has been stable for me, as I haven't seen much downtime. We may have had a little bit of downtime once, but I haven't been in it as much this year, having done a lot of my creation last year. We're currently in a transition stage where I think data governance is returning to their framework.

Alation Data Catalog has kept up well as our organization has grown, since we've been growing pretty quickly and we do keep adding more tables to our data warehouse, indicating that it's kept up well.

I have not personally interacted with customer support at Alation, nor have I really had any conversations with data governance about it.

Negative

Before Alation Data Catalog, I don't think we actually had an official solution in place, as our data governance department was only established a couple of years ago. Being a mid-sized bank, that was a big point of maturity, where we built out data governance, made a plan, decided on which tool to use, chose Alation, implemented it, and then started curating the data.

I think we've seen a return on investment, particularly in terms of the energy from the analysts, as people really have energy around curating their contributions and using the tool. I'm pretty confident of that, but I just couldn't say if it was a measurable return on investment.

I haven't had any experience with pricing, setup costs, or licensing, as I have been strictly an end user and haven't had any administrative or management responsibilities.

I actually don't know if our organization evaluated other options before choosing Alation. I wasn't a part of the conversation for selecting, as that was more related to data governance, and I was strictly an end user after the fact.

I actually don't know which cloud provider we use for our private cloud deployment.

Alation Data Catalog is a great tool, though I don't have any specific advice. I think it's a solid tool for what our organization needed as far as data governance. I gave this product a rating of 8 out of 10.

I have been using Alation Data Catalog for the past year now.

My main use case for Alation Data Catalog is updating data descriptions and making sure analysts have what they need to do their job.

We mainly use Snowflake and DBT to update descriptions and documentation that then gets automatically pulled into Alation Data Catalog for analysts to use.

I really appreciate the lineage functionality that Alation Data Catalog offers.

The lineage functionality helps me in my work by allowing analysts to know how downstream tables are being built and views, and it can also be connected to Power BI, which is impressive.

Alation Data Catalog has positively impacted my organization by allowing analysts to be onboarded much quicker and easier as a lot of their questions are answered within Alation Data Catalog. This lowers the burden of other analysts within the business having to teach and answer queries that would already be answered within Alation Data Catalog.

Some of the downsides about the lineage is that some of the code is quite difficult to read as the formatting is a bit ugly sometimes.

Alation Data Catalog can be improved with the lineage formatting, which is a little bit hard to read sometimes, and there are things like data flow objects where the naming conventions are a bit odd. I believe the catalog sets could be improved since currently, we have a lot of catalog sets just to apply stewards to different schemas, columns, and tables.

From my experience, Alation Data Catalog is stable.

Alation Data Catalog's scalability is really good since everything is cloud and everything gets pulled into the system via Snowflake and DBT automatically.

So far, customer support from Alation is good; we have been able to contact them, and they have been able to help us whenever we have had issues, as well as made some improvements from our feedback.

Positive

We did not previously use a different solution.

I was not personally involved in the setup of the pricing for Alation Data Catalog, but I do know that we were awarded or given a lot of free viewer licenses, which helped a lot.

I have not seen a return on investment, and I have not measured those things yet since we have not had it long enough; it still takes quite a bit of time to update and sell the product to the business.

I was not part of the discussions before choosing Alation Data Catalog, and I do not think there were other options; Alation was the only option.

My advice to others looking into using Alation Data Catalog is to sort their metadata out in Snowflake and their source system first before developing any connections to Alation.

My company does not have a business relationship with Alation other than being a customer.

I gave Alation Data Catalog a review rating of 9.

My main use case for Alation Data Catalog is cataloging various business domains, technical metadata, and business metadata for them.

I use Alation Data Catalog for cataloging business domains by cataloging different data sources, such as Snowflake, Power BI, Informatica, and DBT, so we integrate these sources with the business domains.

We use the Alation Data Catalog cloud version, ACS, and we utilize its lineage, its governance techniques, and as well as its cataloging of metadata objects.

The best features Alation Data Catalog offers include data discovery, data cataloging, data storage, technical and business metadata for your business domains, and lineage for data flow visibility.

The data lineage feature in Alation Data Catalog gives an idea of how the data is being transformed from different sources towards the end product, to the data product level, which helps my team day-to-day.

Data discovery in Alation Data Catalog allows me to access all the data within the different data sources with a single click. Alation Data Catalog has positively impacted my organization by improving the data marketplace section, the data utilization section, and the quality of the data.

There has been an increase in data usage and also time is being saved as specific outcomes related to those improvements.

I notice a couple of pain points with Alation Data Catalog: they can improve on the lineage perspective and improve their data sources integration.

They can improve the search capabilities for the data.

I have been using Alation Data Catalog for a year.

My advice for others looking into using Alation Data Catalog is to try to utilize the data discoverability, data profiling features, and improve the data quality features of Alation Data Catalog.

I think it is a good cataloging tool for governance activities. I would rate this product an 8 out of 10.

We do the integration work for our multiple clients. Their problem is that many of their legacy systems lack a defined data or business glossary for their data attributes. First, they want to build a data catalog with a proper business glossary. Second, they aim to establish data lineage to track their data's transformations. Lastly, in some cases, they want to integrate data quality rules or business rules across the platform using Alation. These are the three main use cases they are looking to address.

The most valuable feature is cloud integration. It can automatically crawl and index various data sources on-prem or in the cloud. With 70 to 80 percent of enterprises operating in the cloud, the automatic crawling feature has proven to be one of the best.

When issues arise, two key concerns arise. First, how can we perform root cause analysis faster? Second, how can we optimize resource allocation, considering the associated costs? Every customer is focused on reducing the cost of computing and resources deployed in the cloud. These two aspects should be more stable. In a nutshell, data observability within Alation would be incredibly helpful for addressing these challenges.

I have been using Alation Data Catalog for ten years. We are using solution V 2024.3.

The initial setup is easy. If the business rules or governance policies are already drafted, implementing them for one system might take around six weeks.

 We work with the data governance team to configure the necessary rules and set up crawlers and workflows. 

I rate the initial setup an eight out of ten, where one is difficult and ten is easy.

We have a separate team of admins who take care of the installation. It's quite friendly.

The key aspect is ensuring that any policy changes in data governance are translated into rules within Alation. For instance, if a new attribute, such as a private one like SSN, is added to a database, and a policy mandates SSNs be masked for the first eight characters, Alation will enforce that rule uniformly. This ensures that all SSN information columns are properly masked and aligned with the governance policy.

Data discovery is best achieved through crawling. If we need to build lineage around it—tracking how data flows from one system to another—some of that is automated. 

With Alation in place, from a business user's perspective, if they need to derive a calculated field, the system helps track where the data originates. The entire transformation is captured in the data lineage from the source to the actual KPI value. This often involves multiple systems where the same attribute might change. Lineage becomes especially important during regulatory audits, where you're asked to explain how a KPI was derived. If the lineage is built into Alation, retrieving and providing that information is accessible. Without it, you'd have to analyze how the KPI was calculated each time manually.

Overall, I rate the solution an eight out of ten.

We try to federate Alation Data Catalog from different parts of the project onto one platform.

The solution's most valuable feature is the ALLIE AI feature. The features are generally the same across all data governance tools I've had experience with, including OpenMetadata, Alation, and Collibra.

We have had issues setting up the connectors and getting Alation's support team to resolve issues.

I have been using Alation Data Catalog for six months.

Alation Data Catalog provides good stability.

I rate the solution’s stability an eight out of ten.

I have previously worked with OpenMetadata and Collibra. From my reading and research knowledge, Collibra seems to be more stable on the connectors and security side. I still have to explore Collibra's federation part. Collibra is already FedRAMP certified, whereas Alation Data Catalog is in the process of attaining its FedRAMP certification.

We saw a return on investment with Alation Data Catalog on the federation side. We could bring everything to one place for the organization to know about the data assets, and the solution helped us integrate the knowledge.

I don't have all the details on the pricing side, but the solution was more expensive than originally expected.

On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing an eight out of ten.

I haven't explored the solution's data lineage capabilities much. However, I have heard that there are some difficulties with getting the lineage to work, as it doesn't properly pull the information in. The solution provides automation, metadata descriptions, and tags. I would recommend the solution to other users because it's a stable product and an industry leader.

Overall, I rate the solution a seven out of ten.