Time

4 weeks

Role

UX Designer

Processes

Ideation

UX Research

Wireframing

UI Design

Collaborators

2 Product Managers

1 Data Engineer

1 UX Designer (myself)

Impact

Results of this project

My designs were integrated into the product and are live.

Datasets are now listed as one of the 3 key values of the PLEXOS product on the company's website, which you can view here.

The Problem

Raw data is messy and prone to error, making it challenging to find valuable insights.

Energy Exemplar creates software that simulates real-world energy markets. One of the benefits of purchasing the software is working with data analysts who provide simulation-ready data sets. However, raw data is messy, and prior to this new addition there was no central place for teams to customize or download data sets.

The Data Hub idea was created to give teams the freedom to easily search, save and download data sets, all while maintaining the cloud product's clean and intuitive interface. 

User Research

Who is an Energy Exemplar user?

Who is the Data Hub for?

User Experience

What is the experience currently like?

Complex

The current software was built for data analysts and not very user-friendly, making it difficult to use and navigate.

Linear

Creating a new data set was possible, but finding one you created in the past or managing all of your data sets was not.

Rigid

There was no way to filter for the constraints that we found users wanted, like date and time or region.

Journey Mapping

What is the user flow for creating a data set?

I met with 2 Product Managers and a data engineer to get a better understanding of the user flow. We observed what the essential functions were and the order they were usually done in.

Drag the arrow to view our whiteboard notes.

The Solution

A data hub that allows teams to easily customize, view and download complex data sets.

After meeting with all the stakeholders I started by using pen and paper to sketch out what the solution might look like. It was important that everyone was on the same page and in agreement about what the necessary features were, so I made sure to keep them involved every step of the way with regular meetings.

There were many iterations from testing, working with stakeholders and learning something new each time.

Wireframes

Designing low-fidelity prototypes

I created two versions so I could test the importance of the Data Preview section as well as placement of filters.

Prototypes

Building out the wireframes

After sharing with stakeholders and an Energy Exemplar data analyst I found that the second option was easier to navigate.

Iterations

Feedback I received

Second prototype

After presenting V2 stakeholders wanted to see the entire flow, and also wanted to see what an overlay would look like for the data preview section.

Final Product

Designing the final prototype

This version received approval and has been integrated into the product.

Takeaways

What I Learned

• When designing new tools in an existing product, it's important to stay consistent with previous designs so there's an easier learning curve for users.

• Design for who will actually be using the product. Since this product was designed with data teams in mind, I was encouraged to add more filtering options and more information around what they were looking at, instead of a more simple or aesthetically pleasing UI. 

• Getting feedback througout the design process is essential. I was consistently surprised by what was preferred and what features needed to be emphasized, and was happy to have this input before my final design.