Reltio Data Cloud™

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.

Reltio Cloud is used to handle big data, such as customer data. It is very useful for managing data and is mainly known for the unification of data, where the main purpose is matching and merging data from different sources. When both data sets seem identical, we design rules to determine if two accounts or customers are identical. Those accounts will be automatically merged if the rule is satisfied. If the match is only partial, some criteria are met, and the case is flagged as a suspect, it is sent for manual review. This way, we unify the overall data for accounts, customers, or other entities.

For example, a customer with the same name and phone number can be automatically merged into a single entity, along with every other attribute related to that customer. Different approval options exist for merging, such as deciding which customer number or name should be visible to the client. The key feature of Reltio is matching and merging, allowing us to unify data. After that, we can edit, add new attributes, or create new ones by updating the configuration.

We need to write code to create a match rule and everything, but we can still create one without writing code. Even someone working with Reltio for the first time can easily create a complex match rule using their UI.

We can customize anything, including the match rule, server settings, and UI. It’s more like a versatile tool. We also get regular updates to the UI synchronization, and they provide more features with each update, which makes it even more helpful. They also offer support. So when we encounter issues, we can directly contact them, and they will provide support.

There are many issues. For example, sometimes, errors related to tokenization occur while creating a match rule. Many tokens need to be created when setting up the match rule, and we need to influence that process so that no digital tools are created incorrectly.

Another issue is that we are working with around six tenants. Sometimes, there are differences in the UI between tenants with product data. Recently, we had an issue with our lookup (IDM) values. We had around 37 IDM values, but only 20-22 records were shown in the dropdown when creating an app. We had to type and search for the rest of the records. When creating customer accounts, the client won’t necessarily know the exact IDM value name, so they need to select it from the dropdown.

I have been using Reltio Cloud for two years.

It is stable. If you find any issues, we can contact them for support. I haven't encountered any issues because they handle a huge amount of data—two, three, or even four million records in a single tenant. Sometimes, we might experience some slowdown on the client side.

It is highly scalable. It depends on the different tenants. We support tenants in EMEA, finance, and the US. For the finance tenant, around 10 to 15 users perform regular activities. We have approximately 50 team members working continuously on the platform for the EMEA tenant.

Technical support is quick, especially when they know the solution immediately. However, they may sometimes face difficulties and must consult with the internal development team before finding a solution.

Deployment is quite straightforward. We can easily purchase the subscription product. Reltio provides several subscription plans, each specifying the features included in a particular plan.

It is cost-effective.

We can have data from different sources as we want. Reltio is like a database where the data comes from one source and moves through another medium. In our case, we are using MuleSoft as a medium between our systems and Reltio. Sometimes, we send large amounts of data, like 10,000 or 50,000 records. Reltio can handle however much data we send, but there is always a limitation with MuleSoft. While MuleSoft has limitations, Reltio doesn't, and it can process large amounts of data.

Reltio provides three indicators for monitoring performance: green, yellow, and red. If the tenant is working as expected, it shows green. When a high volume of data is processed, it may show yellow, so we should temporarily restrict usage. Once the data load is processed, it turns green, ensuring performance isn't reduced. If the tenant turns red, it’s a high alert state, and we need to contact Reltio.

I’ve worked with Reltio for the past two years and haven’t seen the tenant turn red. It turns yellow when processing around 15,000 to 30,000 records from a source, but it goes back to green after about 30 minutes to an hour. Overall, the data broker works smoothly, and we haven't faced any significant difficulties while handling most of the data.

They have provided something called Reltio Integration. It's a platform they introduced about four to five months ago. It’s AI-based and helps users quickly solve their queries. Newcomers working with Reltio who might have questions or doubts about the UI can easily find answers through the AI or contact the support team. The AI is also configured to create manuals and has been successfully integrated. They are also continuing to work on improving the AI tool further.

It doesn’t require maintenance at our end. During those times, we need to avoid using the system.

I highly recommend it. One major benefit is that they provide custom Java utilities. These utilities allow us to extract or load data in bulk, which would otherwise be difficult to manage individually. With these tools, we can load or extract data as needed.

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