Reltio Data Cloud™

I use Reltio Cloud  for customer data management, specifically for C-MDM purposes.

Reltio Cloud  offers advantages over competitors, including a dashboard with a good amount of detail that looks significantly better than Informatica or Stibo. I can view the entire records matched for obtaining specific data. Users can check the correct data effectively, and the address verification part is smoother compared to Informatica, which is referred to as address doctor. Even though Reltio Cloud is relatively new compared to Informatica, it definitely has its own advantages.

I would describe the impact of Reltio Cloud's data stewardship on data quality in my organization as significant, particularly for customer and supplier data. If someone wants to manage either organization or personal data, that tool greatly excels in terms of a great UI perspective as well as easily maintainable attributes and the data model itself.

In future updates of Reltio Cloud, I would like to see features such as AI for match and merge, which can create predefined AI address doctors and match and merge for customer data, easily integrated into the solution. Additionally, I would like the introduction of an AI chat agent instead of just a search bar, allowing users to query records based on attributes through a chatbot, enhancing user experience as compared to traditional search functionalities.

I have used it four months ago.

I did not communicate with technical support. I learned from learn.reltio.com, and I found the training material to be superb because there are very few tools offering such detailed explanations within the same training. Unlike Stibo, which breaks concepts into short segments, Reltio provides comprehensive training in one go, allowing users to understand how to operate the tool effectively.

The deployment of Reltio Cloud was quite straightforward and not difficult because they have their own plugins and processes for how to create the solution.

In the installation and deployment processes, it usually goes with three people, specifically engineers.

Reltio Cloud was not purchased through AWS Marketplace  or directly from the vendor. It was already available in my company at that time, so I used the system to showcase its capabilities.

What could be improved about Reltio Cloud was minimal. It was simply a small project without complex data or any significant issues encountered since it was just a POC for the client.

Reltio Cloud easily integrates with third-party tools without many challenges. I had a file mechanism, and it went perfectly fine. Compared to Stibo, which limits data types for uploads, Reltio allows simpler formats such as Excel and CSV, making it easier and slightly faster than Stibo but slower than Informatica.

Given how much I have worked with Reltio Cloud, I would rate it at 8.5, as a score of eight feels fair since there are certain aspects I was not exposed to, considering my four months of experience.

My main use case for Reltio Cloud  is data management for the life science domain.

A quick specific example of how I use Reltio Cloud  for data management in the life sciences domain is maintaining up-to-date information with respect to healthcare profiles.

The process in my day-to-day work involves data ingestion from different sources, bulk loading of data, and automated processes for cleaning and transformation.

The best features Reltio Cloud offers include a great user interface and API support for developers.

What I appreciate about the user interface is that the API documentation is well managed, and the UI is easy to use.

Reltio Cloud has positively impacted my organization by reducing the amount of manual effort needed and making it easy to manage downstream systems.

Since using Reltio Cloud, data updates now take weeks instead of minutes.

Reltio Cloud can be improved with easier integration methods or the ability to read directly from databases.

I have been using Reltio Cloud for less than three years.

Reltio Cloud is stable and very reliable.

Reltio Cloud is easy to scale, but I need to contact the support team for that.

The customer support is adequate, but not exceptional.

I previously used Informatica. I switched from Informatica to Reltio Cloud because Reltio Cloud provided all-rounded support.

Before choosing Reltio Cloud, I did not evaluate other options as that was not under my jurisdiction.

The advice I would give to others looking into using Reltio Cloud is to be somewhat tech savvy. My review rating for Reltio Cloud is 8 out of 10.

I have been using Reltio Cloud  for about one year and a half. My main use case for Reltio Cloud  involves collaborating with a lot of people utilizing Reltio Cloud, and what I am doing is creating Python scripts for getting data from Reltio Cloud through the API. The kind of data I was working with was mostly MDM , Master Data Management, where the goal was to get data from clinics and doctors, all this customer data.

The best features Reltio Cloud offers include a unified Master Data Platform, smart data matching, and merging. Reltio Cloud also has hierarchical matching, fuzzy, exact, rule-based, and automated survivorship and merging logic.

Reltio Cloud has positively impacted my organization because we were able to promote our data and sell data to our customers. This positive impact shows up as business users act directly on trusted data, which dramatically reduces the internal IT burden, a critical factor for our industry.

Reltio Cloud can be improved by providing the possibility to connect with other connectors and databases such as Snowflake , Databricks , and eventually with Azure Data Factory . The needed improvements are mostly about the connectors that Reltio Cloud needs to be able to connect with.

I have been working in my current field for two years.

I believe Reltio Cloud is stable.

Reltio Cloud handles scalability in a satisfactory manner as my data needs grow; it was able to keep up with my increased demand. I find Reltio Cloud's scalability to be acceptable.

I have never had a chance to contact customer support.

I did not previously use a different solution before Reltio Cloud.

The integration process with Reltio Cloud was straightforward.

Before choosing Reltio Cloud, I did not evaluate other options, as it was not my decision.

I would rate Reltio Cloud an eight on a scale of one to ten. I chose this rating because of the potential improvements that Reltio Cloud can provide. The cloud provider used for our private cloud deployment was Cassandra , as far as I know. I find the data quality management capabilities in Reltio Cloud to be acceptable. I feel that the security and compliance features in Reltio Cloud meet my organization's needs, as they are satisfactory. The learning curve for new users adopting Reltio Cloud was easy to get started. I find the performance of Reltio Cloud to be moderate. I would say that eighty percent of the support documentation and resources available for Reltio Cloud were helpful. My advice to others looking into using Reltio Cloud is that if they would like to utilize an MDM , they should also check the benefits of the graphical user interface, which I think is more savvy and easier to depict the data on Reltio Cloud. My overall rating for this product is eight out of ten.

Reltio is a master data management tool. While other competitors are in the market, Reltio stands out as one of the early cloud-native MDM solutions. Before Reltio, many MDM products were on-premises solutions, such as those from IBM and Informatica. Reltio is purely cloud-based.

With Reltio, there’s no need to maintain infrastructure or set up a separate database for customer data, as everything is managed in the cloud. This setup simplifies things for data stewards and the data governance team, allowing them to visually monitor and assess data quality through various charts and dashboards.

Reltio also offers features like match, merge, and survivorship tools, which are standard in MDM solutions. Its cloud-based approach has proven user-friendly and scalable compared to other MDM tools.

Reltio has two main aspects: one is handled by developers and architects, and Reltio manages the other. Developers and architects are responsible for configuration, developing requirements, and working on the implementation.

There are default limitations and considerations. For instance, Reltio can store a maximum of 200 values for a single attribute. If your data exceeds this limit, you can request Reltio support to increase the limit. However, be aware that increasing this limit may impact performance, potentially slowing down data loading times.

In cases where attribute values or record counts exceed the standard limits (e.g., more than 20 million records), Reltio support can add additional resources to your tenant. This usually involves extra costs, but it ensures the system remains efficient and scalable. As a developer or architect, you don’t need to manage this process; Reltio support handles scalability and resource allocation.

Reltio Cloud provides a couple of options for developers. One way is by working with an internal JSON file where changes can be made and reflected directly in Reltio. The second method is through the Reltio UI, where developers can modify components like the UI, data model, or data quality. Initially, the UI was limited in features, and although it has improved, not all functionalities are available through the UI yet. Reltio focuses on enhancing the UI to make it more user-friendly and developer-friendly. This transition aims to simplify configurations and support no-code and low-code development.

I have been using Reltio Cloud for five years.

Reltio Cloud is very stable and reliable. When certain challenges arise, or some features seem unavailable, we contact Reltio for support. From a stability perspective, it is highly dependable because it's hosted in the Cloud, ensuring consistent uptime and availability.

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

It takes time to load when there are a lot of sources contributing data to a particular record.

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

The response time is quite fast. They typically acknowledge tickets within five to ten minutes. While their knowledge is generally good, issues sometimes arise due to product limitations rather than a lack of expertise. When such limitations are identified, they involve their internal engineering team to address the issue. This may result in a bug fix or a product enhancement that could take a few months to be included in a future release.

I haven't observed any significant knowledge gaps in their support. If junior resources handle a ticket, they involve more experienced developers as needed.

The initial setup is straightforward. When migrating components, such as data models, UI models, data loader mappings, or data exports, you can export them from the lower environment and import them into the higher environment without downtime. Although Reltio Cloud remains operational during migration, we recommend informing end users of a potential downtime window of a couple of hours. This precaution manages expectations and addresses any unforeseen issues that might arise, even though the platform is generally expected to function normally during this period.

Reltio stands out because it offers extensive real-time integration capabilities. It can be easily configured with analytics tools like Databricks and Snowflake, allowing seamless integration. While Reltio provides simple charts and dashboards for data visualization, it also offers an optional analytics tool. You can use or integrate Reltio's analytics tool with other tools like Snowflake. With the Snowflake connector, any changes made in Reltio are reflected in Snowflake in real-time, ensuring quick updates.

For instance, if a team has a member with extensive knowledge of Intellitivo, this can be beneficial. In master data management projects, match and merge rules are crucial, and having experience in this area is essential. Whether someone has experience with Reltio or another MDM product, familiarity with match rules is important. However, training and experience are also necessary to ensure accurate match rules. Without this expertise, the project could face significant issues. As master data management projects can be quite complex, prior experience is valuable before starting with Reltio.

I recommend Reltio to anybody who wants to implement their master data management project.

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