A day of data scientist
By Hetvi
Hello peeps ever heard of Freaky Friday? The thing Chris Brown sang about and Lyndsey did an entire movie about. Yeah that one! I had a freaky Friday experience and guess who did I wake up as…
NO, not Bill Gates.
That is too good to be true. I woke up as Dave, a data scientist! (It was an anticlimax for me too)
Let's start with understanding what data scientists are.
"Data scientists are like a new breed of analytical data expert. They have the technical skills to solve complex problems and the curiosity to explore what problems need to be solved. They collect and synthesize large amounts of data." That's what Google says.
Coming back to Dave as the day started, the first thing I had to do as a data scientist was to understand the business problem of my client; this involved asking tons of relevant questions, understanding the problem and needs.
The next thing I had to do was data acquisition. This involved gathering data from various sources like web server, logs, database. It is very important to find the correct and relevant data. Hence this step is not just time taking but it takes a lot of effort too!
The following step was data preparation. This consists of data cleaning and transformation. Data cleaning is the most time consuming as you have to deal with missing values, inconsistent data, duplication etc…
Transformation is converting data in apt data structure for the company to understand it easily.
What comes next is exploratory data analysis. In this step variables are defined using which the model is made. If we skip this step we end up using the wrong variable which will lead to an inaccurate model. Hence this is the most important step.
Then I had to get on with the core activity of data science, data modeling. It is performing using machine learning techniques. Here the selection of a model which fits the company most is done. Modeling data is done using python, R and SAS.
The final step is deployment and maintenance.
The selected model is tested and then deployed in the production environment. After this reports are maintained and the project is monitored.
This was my last work for the day.
My day was full of excitement and challenges.
The entire day made me wonder why actually do we need people like Dave? Irony is, spending the day as Dave I also was able to answer my own question. Data science is used in looking for patterns, spotting trends, using it with genetic reactions of drugs and disease logistics can be known. Using data science courier companies find the most efficient path, time and mode of transport for shipping. And many more…
Well it was great being Dave, it made me feel so intelligent. But good days don’t last long nor did this one. By the end of the day I was me again living my boring life, doing my boring work. Nevermind, see you later.
Bye.
