I like that they centralize data management features and combine them with an agentic AI approach in a single platform. It also includes multiple integrations with different sources and delivers good performance. Review collected by and hosted on G2.com.

What I don’t like about ServiceNow in general is the pricing model. It can be hard to know whether I’m really getting a good ROI, because sometimes it isn’t truly measurable. Another point is that putting everything into a single platform is, in some ways, a good thing, but it also creates a strong dependency on them. Review collected by and hosted on G2.com.

I like that ServiceNow Workflow Data Fabric connects and unifies data across different systems, which helps in running workflows smoothly without manual integration. It automates processes and facilitates faster decision-making by pulling the right data at the right workflow and at the right time. The product unifies data across multiple systems without needing heavy custom coding. I find it extremely beneficial in designing workflows that automatically pull the correct information, trigger actions, and keep everything in sync. I also appreciate that it works well alongside other DevOps and monitoring tools. Review collected by and hosted on G2.com.

Complexity of setup and customization, sometimes it takes extra efforts to configure connectors or fine tune data flows. Streamlining onboarding and making integrations lighter would make the experience even better. Configuring data sources and tailoring workflows to our environment required extra effort and extra time. Review collected by and hosted on G2.com.

I love how ServiceNow Workflow Data Fabric helps me pull learning-related data from different systems in real-time, eliminating the need for manual data combination. It speeds up training administration and automates routine tasks. The real-time data access from various systems reduces delays and prevents data inconsistencies, making daily learning administration smoother and more automated. I appreciate the effective automation and AI features thanks to the clean, connected data provided. I really like how it connects to many external systems, keeping the data consistent and reliable, allowing me to focus more on supporting learning needs instead of fixing data issues. Additionally, the integration with internal tools like SuccessFactors helps keep HR and learning data in sync. Once the setup is complete, it greatly helps streamline learning workflows and keeps data in sync across systems. Review collected by and hosted on G2.com.

Sometimes the setup feels a bit complex, and getting everything configured correctly can take time. It would help if setup steps were more guided, since some configurations feel harder than they should be. Review collected by and hosted on G2.com.

I really like the simplicity and transparency of ServiceNow Workflow Data Fabric. The accessibility is fantastic because it democratizes automation, letting process owners build logic visually, which speeds up delivery since you don't need to wait for a developer for every tiny change. I find the efficiency impressive with reusable 'Action' sets that cut down redundant configurations, boosting productivity by not having to reinvent the wheel for each task. Also, the real-time connectivity really stands out as it effectively bridges siloed data sources and workflows, enabling better decision-making. The initial setup was very easy, which was a huge plus. Review collected by and hosted on G2.com.

Nothing, all is good Review collected by and hosted on G2.com.

I like its ability to unify data across multiple systems in real time without heavy data movement. The seamless integration with workflows, strong data governance, and scalability make it easy to build efficient, data-driven processes. What stands out is the ease of integrating with multiple systems through pre-built connectors and APIs, which reduces development effort. On the data governance side, centralized control, data consistency, and built-in security ensure reliable and compliant data usage across workflows. Review collected by and hosted on G2.com.

While it’s powerful, the initial setup and configuration can be complex and time-consuming. Some integrations require additional customization, and monitoring/troubleshooting data flows could be more intuitive. Improving documentation and providing clearer visibility into data pipelines would make it even better. Review collected by and hosted on G2.com.

I like how ServiceNow Workflow Data Fabric seamlessly connects data from multiple systems into a single, unified view. It makes building real-time, data-driven workflows much easier and reduces dependency on manual data handling. Overall, it improves efficiency, accuracy, and scalability across processes. It helps me to see all required data in one place instead of checking multiple systems, so it saves a lot of time. Review collected by and hosted on G2.com.

Some parts still feel complex, especially while setting up integrations and handling large data. Troubleshooting is not always straightforward, need more better visibility on data flow. Also documentation and UI can be improved to make it more user friendly. For large data, performance can slow down sometimes, so better optimization or bulk data handling support would really help. More options for data filtering, batching, and monitoring would make it easier to manage heavy loads. For troubleshooting, it would be helpful to have clearer logs and end-to-end visibility of data flow between systems. Better error messages and debugging tools would save time and make issue resolution faster. Initial setup was not very easy, it took some time to understand data connections and configurations. Review collected by and hosted on G2.com.

I truly appreciate how it unified all of my data from various platforms and allows me to use it within workflows without cross requiring a lot of integration work. I can now access real-time data and make decisions more quickly. Review collected by and hosted on G2.com.

Setting up the platform is a bit difficult, and using it successfully requires technical know-how. Large datasets can occasionally cause performance to lag. Review collected by and hosted on G2.com.

It connects data across silos, so you don’t need to move or copy it. Everything stays accessible in one place, and data flows live into workflows, which means decisions can be made using current information. There are no stale data problems, and no data replication is required, which helps save database consumption. Review collected by and hosted on G2.com.

The implementation can be quite complex, often requiring substantial expertise and a significant amount of time to configure correctly. On top of that, the licensing cost is notably high, which can make it difficult to justify the investment for smaller organizations or teams working with limited budgets. Review collected by and hosted on G2.com.

I love how ServiceNow Workflow Data Fabric creates a 'single pane of glass' by pulling data from different sources like AWS, Azure, and Salesforce without moving or duplicating it. It's a game-changer for me because it eliminates the hassle of managing ETL pipelines. Instead of duplicating massive datasets, I can query the data in place from platforms like Snowflake or Databricks. I also find the initial setup to be easy and hassle-free. Review collected by and hosted on G2.com.

A more intuitive 'guided setup' or template-based wizard for common enterprise data models would help bridge the gap for functional consultants. Review collected by and hosted on G2.com.

It ERP integration Connectors, which allow AI agents and workflows to access, act on, and analyze real-time data from external sources (e.g., Snowflake, Databricks, BigQuery) without copying, replicating, or migrating it. This reduces integration costs, improves data security, and enables immediate, context-aware automation. Review collected by and hosted on G2.com.

Complex Setup and High Configuration Effort: Users frequently describe the initial setup as challenging and time-consuming, requiring significant technical expertise.

High Licensing and Overall Cost: It is often considered expensive, making it difficult for smaller organizations to justify the investment.

Performance Limitations: Review collected by and hosted on G2.com.