Lead designer - user research, end-to-end design process & implementation support.
Design lead, Product Manager, CTO, Developers, Architect, UX Designer (me)
3 Months
Netenrich is a SaaS company that focuses on IT ops and cybersecurity. This project was a redesign of an existing node-based data visualisation tool to improve the overall user experience. I focused on defining the functions, micro-interactions and overall visual design.
Unfortunately, due to NDA restrictions, I am unable to share the details of the project. This page contains a brief overview of the project but doesn't reflect everything I worked on— please contact me for the complete portfolio walkthrough :)
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This was my first project leading the entire design. When this project was first introduced to me, the entire feature seemed intimidating and complex. Asset management and AIOPs require deep subject matter expertise.
So my first step was to gain a basic understanding of what the user’s needs would be and what this feature was to be used for. I aimed to simplify and abstract the concept, so I had enough context to focus on the UX.
Through demos and interviews with stakeholders, I understood more about the product. To put it into simple terms, this visualisation tool for complex data helped users find connections between data. “Investigations” as the name suggests, was used to investigate. Users would look into incidents and other events within a certain timeline and discern which assets were involved and what incidents were linked. Users could then take specific actions, such as creating an incident or jumping into the incident resolution.
1. Empower analysts to figure out root cause of alerts.
2. Explore or investigate certain issues from a certain timeline.
3. Allow users to take actions specific to the different type of nodes.
4. Provide ability to collaborate with other stakeholders.
Unfortunately due to changes in the priorities of the business roadmap, the feature was used mainly for demos and by some internal users. A more granular version of the graph was recently integrated with the incident resolution solution.
1. Evaluate cross-functionality: While this feature was designed to work as a singular module by itself, it had much potential to be integrated within various other offerings in the platform. I would work with the product team to create more specific user scenarios.
2. Accounting for large-scale networks: For MaSPs the network was of a large scale and thus resulted in data overload. Even with the query builder, only the usage of filtering helped the graph become comprehensible. Testing the graphs with different data sets and de-cluttering the chart by grouping nodes is something I would have focused on.
The product itself is iterative and launch doesn’t mean all features have to be launched at the same time. Old ideas are revisited and features are staged out as and when the need arises.
One doesn’t need to be a technical expert to advocate for the user. Although the features are domain-specific, many interaction patterns are often common across different products. One can enhance the overall experience in a complex domain by focusing on the user needs.
