Time ago, I had the opportunity to go to the IES IEEE 2025 occasion. There, I fulfilled many exceptional people from various areas and nations. I also had the chance to briefly fulfill Prof. Yusuke Takahashi, a lecturer and business owner from Musashino College. The meeting was just a simple introduction, yet he kindly provided me his calling card and motivated me to reach out if I wanted the field of information.
For me, that straightforward moment came to be a crucial beginning point. I started to review the trip I have actually taken– via my researches, research, and internships– which I recognized are all interconnected and can work as a foundation for approaching a new course: information scientific research.
This short article is my very early reflection. I am not creating it to suggest that I am already a specialist, however instead as a recap of my understanding process– linking different experiences and trying to see just how each of those dots can create an extra full picture.
Starting as a QA: Seeing Software Program Seriously
My trip began when I worked as a QA on my university job, which I later continued as a teaching fellowship in a firm. My major responsibility was to evaluate software program, discover pests, ensure security, and consider circumstances where the system may fail.
Below, I found out a mindset different from the majority of developers– or perhaps as if being their “adversary.” A QA does not concentrate on “making something work,” but on “just how something can stop working.” This skeptical perspective honed my interest to detail.
I still remember one experience when checking a deal module. Functionally, it functioned well. However, when checked under hefty data lots, its performance dropped considerably. From that moment, I discovered that the quality of a system can not be measured only by whether it works or otherwise. There are various other dimensions: efficiency, reliability, and also customer experience.
This important believing practice became something I carried with me when I started to understand ISO/IEC 25010 This typical emphasizes that software application quality consists of many aspects: use, reliability, security, and extra. QA became a portal for me to recognize that software application should be reviewed multi-dimensionally.
Shift to Item Owner: Looking at Worth
After QA, I continued my teaching fellowship as a Product Proprietor (PO). This shift was rather tough due to the fact that it was something brand-new to me. The mindset was different: QA concentrates primarily on technological details, while a PO must consider the larger image– what worth is truly preferred by individuals?
As a PO, I frequently stood in the center: connecting with designers, QAs, and clients. The primary difficulty was exactly how to combine different viewpoints. I recognized that a feature might look “great” to a developer however not always appropriate to customers.
Below, I began to learn the principles stressed in Lean UX. Lean UX shows that item success should not be determined by the variety of attributes (result), yet by the real worth experienced by customers (result).
I once faced a scenario where the group was active developing added functions. Yet, when examined with individuals, those attributes were rarely used. From this, I understood: structure systems without sufficient validation only adds intricacy, not solutions.
Double Ruby: Framework in My Thesis
I am genuinely thankful for my job experiences since they straightened well with my thesis study, which used the Dual Ruby approach. This model stresses four stages: Discover, Specify, Develop, and Supply.
I used it in my research to layout and develop an IT Asset Administration application for a federal government agency. In the Discover stage, I promptly discovered the core issue: although a system currently existed, staff members still often taped possessions by hand. The factor was straightforward– the system was taken into consideration cumbersome, misaligned with process, and difficult to use.
The Specify phase helped me realize that the core problem was not inadequate functions yet instead usability and regulative compliance. From this, I found out exactly how important it is to specify troubles greatly to ensure that options can really address them.
In the Develop and Supply stages, I involved real users in the version procedure. I applied Lean UX concepts right here by conducting quick recognitions and collecting direct feedback. The outcomes were blended: some parts of the system effectively improved efficiency, while others still needed adjustments.
ISO/IEC 25010: A More Comprehensive View of Quality
In my thesis, I made use of ISO/IEC 25010 as an assessment framework. This basic divides software program high quality into 8 vital features: useful viability, use, integrity, safety, maintainability, mobility, compatibility, and performance effectiveness.
This structure assisted me understand that software is not just a collection of code that “runs.” Its quality must be assessed from multiple point of views.
The outcomes of my evaluation were fairly interesting:
- Performance was good– all core includes worked.
- Reliability was additionally high– the system remained stable even as users enhanced.
- Nonetheless, usability was the powerlessness. Lots of workers considered the system somewhat understandable yet still misaligned with policies, and they felt extra comfy making use of the conventional handbook technique.
From these searchings for, I learned that system failing typically does not originate from insects but from poor customer experience. This information after that became my basis for stressing the significance of an alternative method to software application development.
Seeing Patterns Beyond Modern Technology: Real Estate Representative
Remarkably, after my QA, PO, and thesis experiences, I additionally worked in what seemed to be a really various field: property. The major factor was easy– I have always enjoyed getting in touch with individuals and defining their needs. Initially, I believed this had absolutely nothing to do with technology. But remarkably, there were lots of relevant lessons, which is why I chose to include this in my reflection.
In realty, I discovered to check out “data” that does not constantly look like numbers. It could be client preferences, the level of rate of interest shown throughout discussions or brows through, body language during house trips, and even shifting market fads. I discovered that intuition should be paired with data-driven monitoring.
As an example, not every residence that looks “great and lavish” markets swiftly. Factors like place, access to transportation, and even customer depend on (such as feng shui, etc) matter dramatically. This frame of mind lined up with what I had formerly found out: the worth of an item is not figured out solely by what we provide yet by how users or consumers regard it.
Attaching All the Dots to Data Scientific Research
When I link every one of these experiences– QA, PO, research with Double Ruby and ISO/IEC 25010, and realty– I see a typical string: the relevance of data in decision-making.
- As a QA, I assessed mistake logs and performance information.
- As a PO, I relied on user comments data to prioritize attributes.
- In my study, I used study outcomes to measure software application high quality.
- In property, I took notice of market data and customer habits.
Every one of this persuaded me that information science is not just a trend but a real requirement. Data scientific research permits me to combine qualitative understandings (as an example, from user research) with measurable understandings (for example, from system logs or market fads).
Influenced by Prof. Takahashi
Past my personal experiences, I was additionally influenced by Prof. Takahashi’s writings on Medium. In among his posts about building AppSocially , he emphasized the importance of very early client recognition. This advised me that product success is not only specified by technology however also by the capacity to listen and learn from users.
His write-up regarding scholarships also offered me a new point of view: that education and learning and study are not merely specific initiatives yet also part of a bigger community. This additional strengthened my idea that data science can be a means to contribute meaningfully to culture, not simply an individual career path.
Representation and Closing
This post was not written to show that I have reached the peak of accomplishment. Instead, it represents my knowing process. I have actually been introduced to frameworks like Lean UX and Dual Ruby, attempted using them in research study and job, and currently I am attaching them with my growing rate of interest in information science.
I do not know precisely where this trip will take me. However I think that by creating reflections similar to this, I can much better comprehend myself, connect diverse experiences, and prepare for the next steps.
For me, this is just the start. There are still lots of points I require to research comprehensive, numerous hypotheses to examination, and many opportunities to check out. Yet something I think: creating and sharing are means to expand– not only as a technology specialist yet additionally as a person who seeks to make a genuine payment to culture.