Some of the use cases for Ataccama ONE included data quality, identifying and mapping to Collibra, which was their data governance tool. It was critical for them to interface directly with that tool. They also used Ataccama for connecting to their ticketing system and later for inline fixing of data quality issues, moving them to someone able to take that issue and do course correction.

We used Ataccama ONE to read data from the mainframe for a data quality perspective. There's a significant lack in that area with tools being able to interface with mainframe. MetLife has a diverse environment, including DB2, Oracle, SQL Server, legacy, and vSAN files. Being able to work in these various environments and put them to a single data quality tool was very appealing. Additionally, Ataccama supported AI and machine learning, which was one of the features I liked. Furthermore, we were able to interface bidirectionally with Collibra for data governance, catching data quality issues before propagating through the system.

The interfacing to tools such as Collibra was somewhat cumbersome and required more thought. While it was possible to configure these interfaces, they required some coding. It would be beneficial if these interactions could be more plug-and-play and less code-intensive, making them more efficient and easier to set up.

Ataccama ONE has been in use for over two years. I am not with MetLife anymore, but I know they are still using it.

Ataccama ONE was quite stable. We went through one patch during my tenure, which went smoothly, and the updates were worth implementing, with no significant problems observed.

There was a concern with the architectural team about how much processing Ataccama ONE would need as usage scaled up. I did not experience any problems personally, but I understood their concerns regarding resource usage in the long run.

Customer service was excellent, and I would give it a ten out of ten. MetLife worked with senior developers who made a positive impact on our experience, and I would hope that smaller clients receive similar attention.

MetLife did not use a previous solution. Everything was custom handwritten before Ataccama.

The initial setup of Ataccama ONE was somewhat complex. We needed their technical team involved for setup and configuration, which is common for tools of this complexity. Once set up, adding new data quality elements was straightforward.

The implementation involved Ataccama's technical team as they helped engage with the setup and configuration.

I noticed the data quality issues faced previously by MetLife cost significantly more than the Ataccama solution itself. Legally, financially, and reputationally, addressing these data quality issues was crucial, and implementing Ataccama was a major step for them.

Ataccama ONE was competitively priced. However, MetLife experienced challenges during the legal process of set-up, due to disagreement on certain legal clauses.

We evaluated Collibra as they had just acquired OWL, but concerns about integration and stability with the new acquisition made us hesitant to rely on them as a primary solution. The acquisition came with the risk of developer turnover and adjustments, so we opted for Ataccama.

On a scale of one to ten, I would give Ataccama a high nine. The tool met many of our needs effectively, and the ability to leverage machine learning was particularly advantageous.

The primary advantage lies in the platform's high degree of automation. Supervision requirements are minimal, and in case of any component failure or connection issues, detailed emails promptly notify us about the problem's location and nature. Similarly, upon resolution, we receive email notifications confirming the fix. This automated notification system is particularly beneficial, as earlier versions lacked such features, necessitating constant manual monitoring. With this improvement, we can redirect our attention to other priorities instead of continuously overseeing the platform, contributing significantly to our efficiency.

The desktop version of the solution was particularly valuable to me, primarily for creating components. We opted for the data quality aspect to assess the quality of our data warehouse. The functionalities available allowed us to not only check data quality but also serve as an ETL tool. This versatility enabled data transformation and storage in various formats, including files on platforms like SharePoint or local online directories. The flexibility of the tool catered to the specific needs of those building components, contributing to our desired outcomes.

Speaking specifically about the version we use, version 12.3, I'm unsure if this has been addressed in subsequent versions. One improvement I'd like to see pertains to the language used in certain components, especially in data quality checks. The language complexity posed a challenge for beginners. Although we had on-site assistance from Ataccama, making it manageable for us, some individuals found it difficult to comprehend, necessitating additional support. The provision of a comprehensive guide for on-premise installation can also be enhanced. The lack of detailed information on the solution's workings and the overwhelming nature of notifications, with extensive content, were areas of concern. Streamlining the notification content in newer versions would significantly expedite issue resolution.

I have been using Ataccama for eight to nine months.

We did encounter a few issues, primarily surfacing around two years post-implementation. These were largely related to network issues. Notably, when there were updates to the database, the application, at times utilizing Jenkins, faced challenges with restarts for both the application and the database. While this was the main hurdle, I currently cannot recall any additional significant challenges.

We haven’t applied this solution in a scalable setting, so I can’t comment on this aspect.

We have the customer support, but there is no particular assigned support facility for us.

I played a role solely in the migration process from the old version to the new version and was not engaged in the IT aspects, such as configuring equipment, setting code for installation, managing firewalls, etc. The installation process involved a company called Adastra. They were present on-site for approximately two to three months, overseeing installation, workforce setup, and providing explanations on system operations. Following this period, we solely relied on our in-house team, as we had no ongoing support arrangement with Ataccama.

Our licensing model wasn't user-specific; instead, we paid fees for the engine and maintenance. As we didn't have a support contract, maintenance fees were likely nonexistent. Regarding the upgrade, we had an account for the initial two or three years, and considering the features provided by the solution, the pricing was reasonable.

Ataccama’s website offers comprehensive guides enabling users to acquaint themselves with the solution, its benefits, current features, and future advancements. The guides are well-structured, focusing not only on the data port aspect but also on broader functionalities like data cataloging and data lineage. The solution provides a holistic view of the entire data flow, including source systems, data warehouse, transformations, and relevant details such as why and how changes occurred. For business users, it facilitates insights into data definitions, creators, and modification history. This extensive information is available when utilizing the complete package, distinguishing it from prior versions that primarily emphasized the data quality part.

Based on all factors, I would rate it 8 out of 10.

We primarily use it for data-related tasks, focusing on assessing and enhancing the quality and integrity of our data. Our typical dataset size falls within the range of one to five gigabytes. We employ the platform for tasks such as data mapping and data transformation.

One of the most significant advantages is the ease of creating tables and hierarchies. Unlike SQL, where you need to write complex statements, in Ataccama ONE, you can simply copy and paste data from your documents and quickly generate tables with minimal effort. I found it to be highly deployable, making it a user-friendly choice for our project.

The drag-and-drop feature is incredibly flexible and straightforward. Even for someone entirely new to the tool, it's remarkably easy to grasp. It comes with documentation, which is beneficial.

It is not very versatile when it comes to integrating with Unix and other applications. I believe it would be beneficial if it could enhance its flexibility to connect with a wider range of downstream systems beyond just Excel and Postgres. I would also recommend enhancing the documentation with more comprehensive information that covers the latest features and developments.

I have been working with it for three years.

It is quite stable, with no significant issues or frequent changes.

It would be beneficial to see it evolve towards cloud-based scalability, where it can efficiently handle larger volumes of data, possibly exceeding a terabyte. Currently it is optimized for managing relatively small datasets.

The experience with their support team has been satisfactory. Whenever we reached out to them with inquiries or issues, they were quite responsive. We would submit tickets in the support system, and typically, by the end of the day, we received their prompt responses, which was impressive in terms of turnaround time. I would rate it nine out of ten.

Our deployment approach was relatively straightforward. We created two files and placed them in a designated path, and that constituted the deployment process. It was a simplified and flexible process, especially when compared to other modules and their deployment procedures. If there is a single code change, it can be completed within a few hours. However, when multiple code changes are involved, it can take one to two days, depending on the complexity of the changes and the need to coordinate with other teams.

We evaluated Informatica and Ab Initio.

I would like to emphasize that Ataccama ONE is an excellent tool, especially for those who are new to data management and may not be proficient in coding or SQL. It offers an easy-to-use platform with extensive documentation. It serves as a great starting point for understanding data architecture in a simplified manner. I would rate it nine out of ten.

We are using the product for data quality. We can connect it with data sources, such as Microsoft SQL, Oracle, Teradata, and local systems, including shared drives, to check data quality and profiling. We can also use it to write rule logic as well.

The product’s important feature is data profiling and quality check. To get data quality, we need to collect all data. We have data everywhere, and their initial goal in modern times is to get data quality. We normally ingest all the metadata from the data into Collibra. We need to manually download the report from Collibra and load it into Ataccama. We are reducing these manual steps using the integrators and putting Ataccama and Collibra together. Ataccama can also perform the EDR.

It is complicated to fetch 20-25 reports when we profile the data. We have to raise a ticket to Ataccama's team.

I have been using the Ataccama ONE Platform for two years. We are a customer of Ataccama.

The product is stable. I rate its stability an eight out of ten.

Ataccama has different documents on their side. I rate the product’s scalability an eight out of ten.

Our IT security team manages technical issues.

The initial setup is simple. We are better equipped to handle that connection type when we connect very different data tools.

We worked with stakeholders to clean and profile the data so they could easily analyze it. We have some unrestricted data formats, such as XML or JSON. To redeliver this data, we need to create a plan. It is similar to the previous process, but we cannot perform data quality checks on this type of data. We need to create the data in XML Insight to use data quality checks. There are many functions inside the Ataccama, such as fixing grid files. We can read dispute finance data in the web app and generate reports. Currently, we need to create the component or dispute. Then, the data comes into the room in a stable format, and we can easily upload it to change the data quality.

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