Data science has become a buzzword in today’s world. A graduate fresh from school will have on his CV ‘’proficiency in data analysis’’ I was in that shoe before LBS deflated my capability. Our first class was an excel class, and I could remember the faculty asking us to rate ourselves in excel proficiency- many people ranked themselves above 7, and I think I ranked myself a 6. He smiled because, for him, he was 2- funny, wasn’t it? Your instructor ranked himself 2, and you ranked yourself 6. He gave us a simple formatting problem to sum a data. Several of us tried and tried without success. You could guess what happened next- many people started scoring themselves 0.
He divided the topic into data entering, analysis, and reporting. For data entering, we learned the critical data types: text/strings, numbers, boolean, and formula functions. He went further to share with us the best practices called FAST STANDARD in data entering, some of which are:
- No empty rows
- No empty columns
- One row of header
- No total of sub/total
- Data in a single column
- Variables/categories should be in a single column
- No obstructions around the data
Some were quite strange to me, especially ‘no total or subtotal’, but I know one of the reasons I came to the school was to learn and unlearn what I have learned before. Other aspects of data entering the faculty taught were sorting and filtering, conditional formatting, removing duplicates and converting to a table.
For data analysis, we delved into the nitty gritty of pivot tables- as easy as pivot table is, and I had already used it for nearly ten years before joining the program, there was still a lot to learn. We scratched the surface of using functions: If statement, vlookup, index and Match. He shared an excel bible with us too. The key thing about using excel or other tools is that the more you practice, the better you become at it. In class, it will look easy, but after 1-2 weeks without practice, I’d have forgotten.
The class aims to make us proficient in interpreting data useful for business decisions. While ABP deals more with qualitative data, this class deals more with quantitative data. And yes, excel is not the only thing we will learn in the course; it is the foundation of everything we will learn in the class.
Other topics embedded in the course are probability and probability distributions; inferential statistics- e.g. analytics used in operations like linear regression or supply chain; marketing, such as pricing analytics and distribution chain; finance, such as time value of money, net present value (NPV) and related concepts.
I need to sit back and enjoy the ride. I may be considering a change of career to data analytics. It is the next big thing in almost every sector now. This may be what I will do in my next life phase.
Data is Life