week 4. Briefing’s summarization

To be fair I'm not entirely sure if we're supposed to write a blog this week considering we were having briefings mainly and there isn't much to conclude from it. However, I can use this uncertainty and combine it with the need to summarize the project's requirements. I'll be noting the most important parts that are necessary to focus on at the moment.

As Dr. Pless has mentioned many do not have a definite answer on what kind of data they will use for the project. The same thing applies to our case. Our project is related to the petroleum industry however we are not quite familiar with the field as we are computer scientist students. Therefore, research analysis is required to understand what data is needed and in what shape.

This raises another concern or risk with this data: how to obtain it. Coincidentally, our team has misunderstood the meaning of "risks" in Heilmeier Catechism as we thought they referred to the risks of the end product. Turns out by risks we were supposed to mention the possible issues we may face throughout the project period.

We have spoken to our colleagues at the workplace as we have already mentioned and they cannot provide us the data they have but they assure us that the data provided by the NPD is almost identical. Ofcourse, this may end up with another risk of integration with two different data sources in the future but if we trust each other it should not be too difficult.

Another note that Dr. Pless has mentioned (besides how long some of the presentations were) is that many students do not follow the Heilmeier Catechism structure for the briefings. Not completely sure if this also applies to us but we should work on the presentation's structure and improve it accordingly.

Now the main task we have in our hands is to research what kind of data is required in this particular topic and its shape. Then we need to make sure we can get this data so that we can proceed with the machine learning part of the project.