Thoughts on Finding a Data Science Project. Sometimes you need to let a project go to someone else at work, and that’s okay.
Let’s face it; our projects are our babies. They are near and dear to us, we want to keep working on them, and we see the value in them. Each project adds to the amount we have provided, and we don’t always want to share that work. But what if someone comes up and wants to take your new project from you? Would you let them?
At work, I began working on a project to combine analytic results and analyze their performance in a new way. I thought it might be an exciting project to work on and familiarize me with the analytics we had thus far. As I started this project, I hosted several meetings with different groups of people to understand their use cases and how they would use the code in the end. I wanted to make sure I understood as much as possible to develop the work’s architecture in a usable and expandable way. What I was not prepared for was the last meeting I had on this project.
The last meeting included two data scientists who would be end-users of the code, and one software developer who I thought may have some good insight into how to progress the work forward. I was not prepared for them to step off the meeting and ask for a quick call. This call was to express their excitement at the proposed work and how they felt after finding a passion project that would provide value to the team. After this call, I developed a series of user stories that would be worked on for this feature that they now owned. We met later in the day, and by the next sprint, had planned out how they would begin working on the development of this code.
After many meetings, discussions on the work at hand, and a sprint planning session, the project I thought I would work on was no longer mine. And that is okay. After sitting back and reflecting on this situation, it taught me a few things.
Projects come and go in the workplace, but sometimes those projects go to other developers or data scientists. You need to step back and understand when it is okay to let go and let someone else take on the work. In my case, it was clear that this developer had found something they were passionate about and that they felt could provide value to the team. Instead of keeping the project, I let them take on the work and enjoy it. Understand that these moments will come to you, and you will need to decide on the next steps. Do you give the project to someone else, or do you keep it?
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
Analytics India Magazine brings the list of leading analytics and data science products for the year 2020 that have positively impacted businesses across the globe, helping them make decisions. To source the best 10 products, we reached out to more than 25 companies. Ranging from serving financial sectors to manufacturing, retail, solar and other industries,…
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
Become a data analysis expert using the R programming language in this [data science](https://360digitmg.com/usa/data-science-using-python-and-r-programming-in-dallas "data science") certification training in Dallas, TX. You will master data...
Need a data set to practice with? Data Science Dojo has created an archive of 32 data sets for you to use to practice and improve your skills as a data scientist.