<aside> 💡 Reminder:

This product design is inspired by one of my previous internship experiences. The content is modified and tailored and the original content is bounded by NDA. Feel free to ask about this experience if you are interested.

</aside>

目录

Background

• With the rapid evolution of big data technologies, related processing tools have gradually shifted from pure command-line interfaces to more user-friendly GUI. Leading tech companies such as Amazon AWS, Google Cloud, and Microsoft Azure have all introduced big data products with Web Console support.
• However, for many non-specialists and data engineers or analysts who prefer graphical interaction, these products still primarily focus on basic data processing functions. They often present user challenges such as fragmented system management, high technical barriers, and complex interaction processes, limiting broader accessibility and usability.

Problem Statement

How Might We？

• Targeting engineers across internal business units as well as potential external enterprise users, we set out to design and develop an efficient, intuitive, and user-friendly big data processing product. By leveraging technologies such as data lakes, the product empowers users to access, explore, and extract greater and deeper value from big data with ease.

Exploration

Background / User

User Interviews

I don’t like a lot of coding and I am not an expert in that. I prefer drag and drop interfaces. — A Senior Data Architect

— 我不喜欢写代码的。我是喜欢是拖拖拽拽就好了。你们这种比较擅长写代码的可能喜欢命令行。 — 我不擅长的，我最好不要写代码。我也最好这种图里拖拖拽拽就好了，比较简单。

Survey

• For the top 20 clients of existing big data products, we designed a survey focusing on their current self-service experience and usability challenges, aiming to uncover pain points and opportunities for improvement.

Persona

• Thomas, Data Engineer
  • Daily work: Designing and building data pipelines; monitoring and debugging existing pipelines; preparing processed data to support data analysis and downstream use.
  • Pain points: Heavy workload; time-consuming debugging; fragmented and inconsistent systems; difficulty obtaining reliable and actionable system information.

• Jenny, R&D Manager / Resource Owner
  • Daily work: Supporting team members in problem-solving; planning and managing project workflows; recruiting and team building.
  • Pain points: Overloaded with tasks; little uninterrupted time for independent work; frequent coordination across multiple teams, stakeholders, and resources.

The Process