Alation Data Catalog Reviews

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.

We primarily use the product as a data catalog tool to search for data assets like tables or columns.

The platform's most valuable features are workflow automation, automated business metadata tagging, technical metadata tagging, and data integration with data quality tools or platforms.

The product's data governance features need improvement.

Our company has been using Alation Data Catalog for the last three years.

We encounter a few system outages. However, it might be because we have deployed in on-premises infrastructure. I rate the stability an eight out of ten.

The product's data migration from on-premise to cloud infrastructure is not seamless. I rate the scalability a six out of ten.

The technical support team takes longer to respond than expected for simple issues.

Neutral

I have used a different solution in my previous organization.

I was not involved in the initial setup process, but I think it was not that complicated. It took less than a week to complete.

Alation Data Catalog generates a return on investment for our organization.

The platform is moderately expensive compared to the other competitors in the market.

We are evaluating different vendors. In comparison, Alation Data Catalog is not performing that well and is moderately expensive.

Alation Data Catalog has improved discovery by addressing and searching particular data, including systems, tables, and columns. However, it could have been more helpful in the data governance aspect. They are about to introduce more features in that area. Its knowledge community is active; I rate it an eight.

I rate the overall product a seven out of ten.

We've recently onboarded the Power BI reports, and the inbuilt connector had an issue wherein it was not scanning the custom pages of Power BI. There's a mandate in our organization that details of the report will be on one of the custom pages. So we onboarded the custom page as well, and we have successfully achieved the task.

The most valuable features of Alation Data Catalog are the simplicity in onboarding data sources, the security in securing the data sources, and the way the various users of Alation Data Catalog communicate with each other through a messenger.

Alation Data Catalog cannot scan the custom pages of Power BI. Having the capability to scan the custom pages of Power BI would be a great feature in Alation Data Catalog. Alation Data Catalog does not provide end-to-end data lineage. It cannot provide a data lineage where the data is going from one data source to another. Alation Data Catalog currently lacks these features.

I have been working with Alation Data Catalog for three years.

Alation Data Catalog is a stable solution.

Scaling up was not easy in the earlier versions of the solution, and it used to crash. However, with the new updates provided by Alation Data Catalog, it is easy to scale up.

As an application support team or application admin team, we are two people using Alation Data Catalog in our organization.

I have been working with Alation Data Catalog's technical support for many years, and I've had a very good experience working with them. They are very proactive and respond to you on time.

Alation Data Catalog's initial setup was pretty easy. The solution provides a detailed step-by-step approach to implement and build the solution. The solution is deployed on cloud.

Alation Data Catalog's basic features and software took around 12 to 13 days to deploy. We were able to onboard a few of the data sources within the next four to five days. In approximately 20 days, we were able to implement and deploy the solution; and onboard around 10 data sources.

I'm working with the latest version of Alation Data Catalog.

I have seen many tools, and Alation Data Catalog is far better than other data catalog solutions.

I recommend every user go through the Alation Data Catalog courses. They have very well-defined videos explaining all the features of Alation Data Catalog.

I won't say that Purview has more features than Alation Data Catalog, but customers tend to go for Purview if their platform is on Azure Cloud. Purview won't be expensive if you already have an Azure membership.

Overall, I rate Alation Data Catalog an eight out of ten.

The tool's metadata cataloging is the most valuable feature. 

The tool's domain model needs to be changed. 

Alation Data Catalog is stable. 

The solution is scalable. 

Alation Data Catalog's deployment is easy. I rate it a nine out of ten. Deployment takes only two to three hours to complete. One to two resources are enough to handle the deployment. 

I rate Alation Data Catalog an eight out of ten. 

We're a superannuation organization, so we deal with people's pensions. We invest their money for retirement. Our users are mostly core data management professionals, including business analysts, data analysts, architects, engineers, and BI developers. There's also a handful of consumers who view content. 

We're working with a range of stakeholders and data sources, and we haven't covered all of the organization yet. But most of the key ones are embedded into the tool. We've built up the catalog through agile iterations or sprints. We're working with the business to understand the information, curate it, and embed that knowledge into Alation Data Catalog so that it's available to those people to support their data use cases.

We had no data catalog beforehand, but we're coming from a very mature environment. Before we had the data catalog, there was no mechanism for users to quickly find data, understand it, share their insights, or collaborate with others. It was very much a siloed approach. If we wanted some data, we just had to rely on people who had some knowledge to point us in a direction. 

We had no idea whether that was enough to support our need and didn't know if there was something else out there in the organization that might be better suited. It was very immature. The catalog now provides an opportunity for people to come together, to share, to find. We had nothing before, so we can't compare anything we used before with what we've got now, but what we've got now is infinitely better.

We capture metrics at two levels. One is to monitor the health of the catalog. That's more for our purposes to ensure that the information we're publishing is of good quality and aligns with what the users need. There are several metrics that we developed primarily to determine how healthy the catalog is and how close we conform to our own standards.

The other set of metrics is used to measure adoption: how many people are using it or the number of new users over time. And we see that growing and growing. It's probably not at the level that we'd like. It doesn't cover all of our stakeholders, but we're getting there. So we're measuring adoption, the number of users, the number of times people are coming back to the catalog, and the number of times they've contributed. When I say "contributing," I mean conversations, developing articles, suggesting areas of improvement, etc. We measure how much they interact with the catalog.

I can't say it reduced our workload. Our workload has increased because we need to get the catalog to a state where BAU can manage itself. There's an awful lot of work that my team is doing to get it to the point where we can relax and focus on other things, but we knew that going in. We knew we had to invest a significant amount of effort to reach a point where the catalog could produce some business value. It's increased our workload, but it's necessary. In another three to six months, we'll be at a point where the changes will be more BAU rather than development or implementation.

I wouldn't say that it helps us deliver our product faster either. Our products are superannuation services. Product analysts use the catalog to understand the markets and the channels they should be targeting, whether it brings a product or service to life quicker. I don't know, but our product team responsible for product management certainly uses the catalog more for insights.

Alation Data Catalog has also helped in terms of compliance and data governance. At data access points, it minimizes the risk of people developing their own repositories and using those repositories for unauthorized purposes. It's more helpful for operational efficiency, leveraging other people's knowledge, and reducing the risk of decisions based on low-quality or unsuitable data.

Our compliance team didn't use the catalog that much. Their focus is ensuring we have appropriate controls and those controls are complied with. They're not heavy data users, as such. They make sure the data users are using the catalog according to various policies and standards. However, it is helping the data consumers understand what data they're accessing, particularly around privacy.

In addition to finding the data, they can also see who owns that data or who knows about that data. It provides guidance in terms of its sensitivity. There's a confidentiality classification in there that provides policies, directions, or guidelines on handling information at different levels of classification. 

Given the relatively low level of maturity, Alation's most relevant feature at the moment is a user interface that's easy to navigate, which helps us find and understand the data. So while Alation has a lot more functionality, our pain point right now is being able to easily find, understand, and trust the information to use it. As our user base grows accustomed to the tool and their capabilities increase, we'll be able to use things like lineage, visualizations, and stuff like that. We have a plan that covers a couple of years, but right now we're just concentrating on just being able to support their critical needs.

We're not using the Alation data governance app at all yet, but we're interested in it. I think it only came out in 2021.3. At the time, it was only limited to Snowflake, and we don't have Snowflake in our organization. So we're waiting for it to mature and grow to a point where we can actually start using it, but we're still interested in its capabilities. I think it could help out in data governance across our tech stack.

The Alation Data Catalog allows users across or organization to efficiently search for and discover data regardless of their location, but we haven't opened it up to the whole organization. We've just focused on those data consumers who work with data every day because it's their job to produce reports, drive insights, etc. So there are our heavy users, and there are other users who look at our dashboard once a month. We haven't really opened it up to those users yet. We will eventually, but we're just focusing on those critical data consumers at this stage.

Alation Data Catalog doesn't support end-to-end lineage. By that, I mean the ability to trace the movement of data from when it first comes into our organization to where it's consumed. Along the way, the data is stored in different places, transformed, aggregated, etc. The journey can be quite a long one from the perspective of a single piece of data, so we needed to track the lineage, and it didn't work as expected. It worked in parts, but it wasn't end-to-end. And we've had to rely on some workarounds to overcome some issues and still not where we want it to be. We understand that there's a lot of functionality coming up that we'll just have to wait for.

When we purchased the tool, we knew that Alation was innovating and would be releasing new features and functionality every quarter. We were more excited than we would be about a stable product that puts out one update per year. And we knew we would find areas where Data Catalog either couldn't support a use case or we had to do a workaround. That has been the case, but Alation has been fairly quick to show us where these fixes or features will come out on their product roadmap. 

We've only had to rely on them a couple of times to provide workarounds for alternative solutions or options. However, that might be more tactical in nature rather than getting to what we want to do. There have been points where we haven't been able to do exactly what we want to do, but we've always been able to work around these issues or wait until the features have been made available.

That lineage would be an excellent example where it didn't support our requirements out of the box from day one. But it's been a journey where we've understood what they've released, how it worked, what doesn't work, what's coming up, and when we'll be able to kick that off again.

We started in April of 2020, so we've been using Alation for about a year and a half now.

Alation's stability has been fantastic. We've never had an issue with it going down. It's obviously maintained from an infrastructure point of view. Alation has monitoring and alerts. We do version upgrades every quarter, and so we have to restart it after that. But we've never had any issues with reliability.

In terms of how extensively we plan to use Data Catalog, we're only about halfway there. We're deliberately focused on some critical use cases, but there are others out there. For example, there are our finance and investment teams. We've still got to plug them to a certain degree. I'd say half of the staff is using Data Catalog now. The journey has still at least another year to go to get us across the organization to a point where I can tick it off and say, "Job well done."

I rate Alation support nine out of 10. I've had no issues with them, and they've always been able to assist us. They're innovating at a high rate, so we've had several technical problems where we've had to ask questions about the APIs and various other technical things. They've always been reasonably quick to get back to us with solutions or workarounds.

The documentation is also excellent. The only tricky part has been the time zones because we've got some tech folks here in Australia and some in America. It's a matter of just fitting the time zones to get answers. They're timely in their response, though. I've never really had to have conversations with a client manager about the performance of their tech support.

Positive

We had a bad experience with another catalog from a different vendor called Talend Data Catalog. They were partners offering data integration tools, and they acquired a data catalog. Since the data catalog came with it, we thought we'd try it first. We had a six-month trial or prototype, but it didn't support many of our use cases at all. It was frustrating, so we decided not to implement that part of their suite, and we went back to the market again. 

The experience gave us a lot of insight into what we needed from a data catalog. At first, we took it at face value that it would work. The second time, we researched the Gartner analysis of the types of vendors, functionality, and scoring on the assessment template.

Data Catalog's initial setup was pretty straightforward. With our three-year license, we also purchased the Right Start program, Alation's program to help clients get up and running quickly. It's a hand-holding exercise over several weeks, and we have to do it remotely, which adds to the challenge. Next, we stepped through the various processes to prepare for installation. There's the installation, configuration, and getting our first couple of use cases working. 

In total, it was about a three-month process. It's a planned program of work that takes us through different things and gets us to a point where we can prove that the software works in our technology environment. That was very important, and it gave us a bit of an insight into how easy it is to navigate, configure, and set the tool up. It is easy to work with and navigate compared to some of our other tools. It was pretty seamless. 

It took more than a quarter, but I didn't mind that. If you get someone there full-time working with it eight hours a day, it's easier. It took longer than it would have taken pre-COVID because we were working remotely across different time zones, and their tech team is in America. But we didn't mind that because it gave us time to sit, think, play around, and research. We took our time doing it, but I think it was time well invested.

We set the expectations that the first six months to a year was really about progress. And the benefits would follow that. So we were very keen not to say we were going to get help from day one.

Maintenance has two components. One is the actual infrastructure — the tech stuff — and our infrastructure team manages that. They're involved with version upgrades, monitoring, alerts, etc. We've got a group of dedicated people to manage all of the applications running on our AWS infrastructure. When we have our quarterly updates, it might take them a couple of days to maintain the software.

But my team handles the maintenance of the catalog itself, and we're working on it full time. Including myself, there are three people on the team. There's one guy full-time on it and another guy who works on it part-time across other tools as well. We've invested a lot of time getting it to that point. "Maintaining" is perhaps not the word. We're building it out. We're building it to the point where we can maintain it. I don't contribute that much other than planning, prioritization, decision-making, and things like that. And then, there are two other full-time staff members within data governance.  

We had a long-term vision for implementation when we deployed Data Catalog. But we just needed to get the tool in place and play around with it before confirming what we could and couldn't do. We worked with Alation to determine the sequence and get to a point where we could move forward independently. That was important. We've relied on Alation's knowledge and experience to get us to a point where we could go live. We're moving forward on our own now, but we still work closely with Alation going forward when there are new features and functions.

We've undoubtedly seen some time savings. We haven't quantified it, and that's probably something I need to focus on. We'll know the exact quantitative benefit at some point, but it's probably saved us time. The analysts spend 80 percent of their time finding the data and 20 percent doing what they're supposed to do. That's been flipped, so finding the data takes 10 to 20 percent of their time, and 80 percent is devoted to analysis. 

I can only describe the benefits, but I can't quantify them. The other benefits include cost savings in terms of repositories. You no longer have to create your own data repository every time you need something, irrespective of whether others have it or whether you could work with something else. And there are obviously storage and retrieval costs there. Now, we're starting to decommission all of these repositories of data, which are being replaced with our authoritative sources or trusted copies of data. 

We're absolutely seeing a return, but we knew it would take time to get to that point. And we were clear on setting expectations, particularly regarding management. I think that's worked. That's allowed us breathing space to get us to a point where we can actually provide benefits. It's hard to quantify them at this point, but it's something we'll need to do. At some point, we're going to need to relicense. Our three-year license is up next year, and I'll have to convince the CFO that it's worth it.

You've always got to understand Alation's pricing model because they have different models. Vendors have various models, and the difference is sometimes quite stark. You've got to understand what currency it's in. A three-year agreement is better than a one-year rolling 12-month agreement from a price point of view. I'd recommend looking at a three-year deal because you can't stand up a catalog and produce value in 12 months. It's going to take a significant amount of work to do that. So you've got to be in it for the long haul and I think most organizations are.

There's a discount, so you'll need to whittle away at them. Ask what their list price is, but figure out precisely what deals they can provide because some of them depend on the time of the year, I think. If you focus on the end of the financial year when they're trying to meet their targets, they might be more willing to extend the discounts. Early on in the financial year, you probably won't be so lucky. Timing is another thing as well. But I would recommend understanding the pricing models, what's in, what's out, and how they can discount it. 

We did a quick scan of the market and limited it down to three. There were the market leaders Alation and Collibra, and then there was a local firm called Alex Solutions. We included them because they were local and just wanted to see what they had in the market. There were also several other solutions that our competitors were using. We got them in to do demos and whittled it down to Collibra and Alation. 

And through that selection criteria, we chose Alation. There were two reasons: cost and user interface. We thought the user interface was easier to navigate, and Alation came up with more significant cost reductions. While Collibra did reduce their price, they couldn't match Alation. 

Alation is easier to use from the perspective of the end-user. They've ensured that the user interface is intuitive, easy to use, and easy to understand, whereas the others come at it from a more technical point of view. They could be quite strong technically, but they might be very hard to use because they haven't focused on that user interface. Alation went the other way around. 

They're building out their technical capability, but I've thought they've always had a very good user interface. And coming from our low level of knowledge or maturity, it was critical that our business users could quickly use and trust a tool. Alation allowed them to do that. Collibra probably could have worked, but it was harder to navigate around, and we thought it wasn't quite so intuitive. So we went with Alation. 

I rate Alation Data Catalog 10 out of 10. I've seen many other data catalogs, and I think Alation is better than all of them. My expectations have been met and exceeded. And they bring out new features and functions every quarter. I've never seen a tool like it. Vendors have been saying they've got end-to-end metadata management tools for years, but it's never been the case. This is a fantastic tool. It's easy to use and navigate. It can do just about anything that you want it to in our environment. I don't know what other technical environments are like and how complex they are, but I'd say it's getting better. 

However, I would caution against expecting benefits from day one. You talk to any sales rep for any tool — whether it's a BI tool or whatever — and they'll always say, "We'll be able to support all your needs within two to three weeks for whatever." I'd be cautious about thinking that Data Catalog can solve all your problems in a short time. It takes a while for new users to understand the breadth and depth of the features and functions, particularly around the machine-learning capabilities and things like that.

Prepare yourself because it's going to be a journey. Prepare yourself for Data Catalog to provide no apparent benefits for some period while you're getting used to the tool, getting it implemented, and building it up. You can't just install it, and it's there. You've got to install it and build up the content to be useful. Otherwise, people will look at it, think there's nothing in it, and they'll never come back to it again. 

So installing it, configuring it, and making it available might be a milestone for tech, but people don't get value immediately. And if they don't know what's in it for them, then they'll turn away. You're probably losing the overall battle if you like. Your success criteria are the amounts of people who use it, come back to it over and over again, and add to it themselves. You need to invest a lot of time before getting to the point where that is the case.

We have one deployment on AWS cloud and our enterprise instances use the Alation cloud.

We use it primarily for supporting our data scientists. We also use it for sharing data governance, document policy information, and data classification information.

Our use cases are for a lot of data literacy and data usability.

We had some of our data science engineers, who had built out some cloud-based data and data products for users. They were spending a lot of their time, up to 30 to 35% of their time, answering questions about the data and helping people understand how to use it. Once they were able to document that information within Alation, they were only focusing on around 5% of the high-value questions that really couldn't be solved through the catalog itself. It freed them up to be more productive, it made their end-users more productive, and it made the adoption rate of their data products rise more quickly because people were able to get to using them.

On the engineer side, they went from spending 25% of their time answering questions down to less than 5% of their time answering questions. They could just point people to the catalog instead.

Alation has increased the adoption in our organization. Using the business-led type of governance, where we're finding the experts where they sit in helping empower them to govern their own data, leads to higher levels of data literacy as self-service data, data tools, and development throughout the company.

It enables users across our organization to efficiently search for and discover data regardless of location. It provides a federated search interface that people can use to search across all of the assets in one day. So as long as we've connected those sources to the catalog, they can use the same search interface and the same types of keywords, tags, metadata fields, to search, to narrow down their searches, and to filter the information that they find, and find what's relevant to them and their needs very quickly.

Alation has not helped to reduce our team's workload on the governance side. The workload is a little bit higher because we're monitoring and curating the catalog itself, as well. But it has lowered the workload of other teams when they're interacting with metadata and they're trying to share information about data.

It has a really great capability to connect pieces of information and people to build out a graph or an ecosystem of the data that's being used; whether it's the system, the people, or the artifacts that are being generated with the data.

It's important to us because one of our key pain points for our data scientist is understanding the context and the data. It builds that context natively into the tool so that's served up to you. You don't have to go looking for that contextual information that you need about data.

Alation's active data governance, as opposed to command and control style data governance, is the way of the future. That's the approach that we have shifted to over the past few years, really trying to use a more adaptive governance approach. Where we're reacting to what the business is telling us we need, instead of trying to dictate how things should be done. It sits nicely with their analyst-focused product.

I know that this has been on their roadmap and they're working on it, but as a whole, there's an untapped reservoir of capabilities within their article features that could be used and built upon.

We've been using Alation for almost three years. 

We found it to be very stable.

We found it to be very scalable. We haven't seen any issues in that regard.

In our corporate catalog, we have on average 300 distinct users monthly. In our enterprise catalog, where we're around 800 distinct users monthly.

Now that we're on the cloud service, they handle the infrastructure pieces there. We do have a server admin dedicated. Then we have maybe 1.5 full-time employees dedicated to it. Although that may be increasing in the near future. It's more for just driving training and adoption. It's not necessarily for maintaining the tool itself.

We will continue to roll it out. We have five different operating companies, so we will continue to roll it out across all of these companies.

Their technical support has been good. It's gotten better over the past three years. There were times where it was a little slow, but they've been taking steps in the past year and a half to really improve the turnaround time on their support tickets.

Neutral

We had a metadata repository called MetaCenter from Data Advantage Group. We switched because it was a very technical, somewhat limited metadata repository tool. And we were looking for something that was more end-user, business, user data, user-focused, and provided a more holistic catalog experience.

The initial setup was easy and very straightforward.

The actual application itself can be installed and deployed within a few hours. But then there is a process of setting up the data source connection and that really varies from data source to data source, depending on the administrative and infrastructure around each of those different types of sources. The actual setup within the tool itself is very simple and straightforward. It can be done by anybody through the GUI. Any kind of delays come from getting the prerequisites in place kind of on your company side, as far as your security needs and things like that.

We see fast time to value by being simple to implement and manage. We're implementing a new catalog now for our enterprise and we're seeing a lot of quick adoption in people who haven't had access to a tool like that in the past.

Pricing might be a little high for the fact that there are different kinds of users. It's taken them a while to get to the point where they're evaluating how to price these different users appropriately.

There are additional costs if you want to use the new apps, like the governance app.

We also looked at Waterline and Informatica Enterprise Information Catalog.

Waterline wasn't quite as mature at the time. It was a newer company. Informatica was really advanced and technically sound but there seemed to be a need to be within the Informatica family of tools to get the most out of it. But it also didn't have the same interactive experience for end-users, where they could easily communicate with each other and share information with each other.

We didn't see significant differences between them in terms of cost. When it really came down to it, we were looking at Informatica and Alation. They were, at the time, fairly similar.

It's a very effective tool but it helps to do pre-planning, have a good rollout, and architecture strategy place so that you can get the most out of it in a staged and progressive way. Start small and focused so you can provide real and demonstrable value and you can build on that as you go.

It's a one-stop-shop type of solution. I would rate Alation a ten out of ten. 

Alation Data Catalog provides a nice interface for connecting to the database, querying the data, and working on it.

Although the solution performs far better in terms of data cataloging, its data governance capabilities need improvement.

It would be helpful if the solution included data classification and an easier streamlining of the process of workflow creation.

I usually recommend Alation Data Catalog to cost-conscious small and medium companies.

The solution's technical support needs to be improved across the board, especially in lineage and other aspects. Sometimes, we find it difficult to identify the people with respective tool knowledge. It’s a bit difficult to identify resources for Alation.

Positive

Alation Data Catalog is another data catalog product gaining momentum in small and medium financial institutions. The solution's data discovery and enabling the data marketplace improves productivity.

The solution has an AI-based metadata curation model, but I'm unsure how effective it is. I know Alation Data Catalog has some AI functionalities that they're cataloging to leverage.

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