Making biGENIUS-X: State of the application and its future

Interview

TG - Thomas Gassmann (CTO)
OH - Oliver Haidutschek (COO & Product Designer)

Q: It’s been a few months since the biGENIUS-X Launch Event in June, what’s new?

TG: We’ve made some improvements in the workflow. In the UI, we’ve implemented more wizards that would help users automate more tasks. There are new optimizations such as automatic relationships creation. A lot of steps are automated, so you have less manual work to do. We've implemented visual modeling capabilities. In regard to the generators, much has been added changed since the Launch Event, especially in the data vault area. We also now support Apache Spark, Databricks, along with Microsoft SQL, and we will support Snowflake in a month or so.

Q: How is the product roadmap planned?

TG: We have two roadmaps: one for generators and one for the UI functionalities. For the UI, we look at what features current biGENIUS-7 (Windows application) users need, and we’d implement them along side new features that make sense in biGENIUS-X. For the generators, we talk to our partners, potential customers, current customers, and specialists in the field, also for example, Gartner to find out what technologies people want to use the most. Apache Spark and Snowflake are the two technologies that came up most often, that’s why we’re planning to work on Snowflake support next.

Q: So what’s in the works now?

TG: For the UI, we’re working on the functionality of linking Projects, where you’d be able to export objects from one Project and be able to use them in another Project. This is especially useful for a data mesh architecture, where you have data products that need to be consolidated. We’re also working on template customization, which is frequently used in the biGENIUS-7, so we also want biGENIUS-X users to be able to customize the generator outputs of their projects.  

"biGENIUS-X is like a workbench, it has separate views for different steps in a user’s workflow, providing a more focused workspace for data engineers or data analysts"

Q: biGENIUS-7 and biGENIUS-X are ultimately very different products, can you talk about what you’ve learned from the Windows application (biGENIUS-7), and what you’ve adapted in the new cloud application (biGENIUS-X)?

TG: We looked at what biGENIUS-7 users have been using the most, we also looked at feature requests that came from them and implement what are most in demand. Of course, we didn’t just migrate biGENIUS-7 features to biGENIUS-X. We wanted to learn from what is fundamentally good in biGENIUS-7, and figure out how we can solve the problems it solves but do so in a new and better way in biGENIUS-X. biGENIUS-X is more user-centric in terms of its UI design. What Oliver does is taking the needs of the end users and make the application as user-friendly as possible while considering their workflow. biGENIUS-X is like a workbench, it has separate views for different steps in a user’s workflow, providing a more focused workspace for data engineers or data analysts, whereas biGENIUS-7 provides one view where all tasks are performed.

Q: How does the UI in biGENIUS-X affect the productivity in a user's workflow?

TG: I think this is most prominent with the wizards, and the automation steps.

OH: In comparison to biGENIUS-7, the UI design in biGENIUS-X focuses more on the workflow of modern data engineering teams, and the collaborative aspect. With the biGENIUS-X Git integration, you can break down a product into features, assign team members to work on these features, then merge these feature branches into the main branch. As Thomas has mentioned, we’ve broken down the huge amount of information into separate views, which is also helpful in this type of workflow, where teams can break their project down into smaller blocks to work on.  

Q: What are the hurdles you’ve had to overcome while making a complex application user-friendly?

OH: I had to understand how current biGENIUS-7 users have been interacting with the Windows application and find out what is the optimal way that they would like to work. I listened to the feedback from our in-house specialists who have extensive knowledge of the Windows application, and I also looked at users' feedback on what their workflows might look like in the future. I then consolidated all this information and tried to make the UI as intuitive as possible by simplifying all these needs, reduce clutter, and allow users to focus on things they actually need. There are sections where they can focus on modeling, sections where they can focus on showing their customers how the data flow or the relationships are going to look, and sections where they can focus on generating and what to do with the data packs. Basically, if there are things that you don’t need right now in this step of your workflow, they won’t be there to clutter your screen.

Q: How difficult is it to learn how to use a complex product like biGENIUS-X?

TG: Like any complex product on the market, it’ll take some training. Concepts like data flows and data flow sets are very specific to biGENIUS. As they exist in biGENIUS-7, it lowers the learning curve for biGENIUS-7 customers in terms of understanding the logic behind how biGENIUS applications work. We have an extensive knowledge base where users can find step-by-step guides to perform any given task. We also have tooltips that direct you to the relevant article from within the application.

OH: I’ve implemented a common design language that makes the user experience intuitive. Everything is logically placed – where to find a menu, how to open and close items, where to edit items... these are all according to a pre-established standard. So the learning curve with biGENIUS-X is not with the UI, but with the business logic that you’d like to use biGENIUS for.  

Q: biGENIUS is a relatively small company consisting of specialists and experts, do you see it as an advantage to work in smaller teams?

TG: I think our processes are very lean because of the small teams, we have in-house experts in different areas whom we work closely with, and we have access to a huge network of consulting partners.

OH: The main benefit of working in teams mainly consisting of technicians and experts is that we can quickly find a solution to almost any technical problem or need. Our experts also understand the consequences of implementing new features, it makes it easier for us as a team to address the pain points. The process of understanding a problem, finding a solution, to putting it into the next sprints is a short and efficient one. This is also beneficial when customers have specific needs, because we can look at the feature requests and implement them in a much shorter timeframe than in larger companies.  

"biGENIUS-X is built in a way that makes it very flexible to be able to support virtually any technology and platform in the future."

Q: What in your opinion makes biGENIUS-X stand out on the market?

TG: For me, it’s the fact that you do not have vendor lock-in. Everything you get from the generators is in native code, so you can use it afterwards to run it, publish it, without any additional tools from our side, even when it becomes necessary to work on a different platform. Also, the customization of the generation, users can extend and adapt the generators to their needs and standards. And of course, the fact that we provide full support for multiple technologies. biGENIUS-X is built in a way that makes it very flexible to be able to support virtually any technology and platform in the future. We just focus on the ones that are in demand on the market.

OH: First, because of the flexibility of technology support, if you work for multiple companies like a consultant would do, once you are trained to use biGENIUS-X, you are able to work with multiple technologies with one solution. Second, we don’t store any sensitive data on our servers, they’re saved in the customers’ Git repositories, providing them with more control over their data.

Use case demo

To see biGENIUS-X in action, you can watch the latest biGENIUS-X use case demo video.