How Excel is Used in Real-World Data Analysis

Hello Plumbers!
I'm between a beginner and an intermediate in data science; It's a shame I didn't pursue this path, having recently completed a Computer science degree. However, over the years, we didn't do much of Excel in our coursework. In Kenya, most colleges do not take Excel as a serious database software to learn; they mostly focus on SQL, underestimating the power that Excel still has. I therefore started a course in data science at LuxDev Academy, focusing primarily on data engineering.
Over the past week, we focused on Excel as part of the introduction. I learnt that Microsoft Excel is a powerful software developed by Microsoft, which allows you to collect, organize, analyze, calculate, and visualize data efficiently(using dashboards for visualization).
You might wonder why I chose Data Science, having been off campus for almost two years now. Simple, I worked for a company that sold School management systems to schools all over the country. Yes, I dealt with chunks of school data, most of which was disorganized with missing values, outliers, and duplicates. In most cases, I had to clean the data and assign primary keys(in this case, student admission Numbers). If I go back in time, with the one week's knowledge I have of working with this tool, my life would be easier.
Data cleaning and validation with Excel in this scenario would have helped me achieve easier sorting of data, well-organized and easy to work with/sort data from any given field in the database. Most companies use this tool for Financial budgeting and reporting, whereby accountants can consolidate revenue and cost data to generate profit/loss statements or forecast cash flow using Excel formulas and pivot tables. It can also be used for Business decision-making; Managers can use it for scenario analysis and decision support, such as evaluating sales trends or inventory levels in a given business organization.
The exciting part about it is that it makes numerical computation easier by working with formulas. Formulas like SUM, AVERAGE, MINIMUM, and MAX were easy to work with since I did that back in high school. The fun part about learning is gaining knowledge on what you weren't familiar with, and the trainer makes it easier for you. To mention a few of these(Logical Functions):
IFAND is a nested condition whereby both scenarios of the conditions must be met. It can be used by an employer to determine employee eligibility to maybe get a bonus.
IFOR is also a logical function where one of the conditions has to be met, not necessarily all, as in "IFAND". It can be used to choose which employees must be laid off if one of the conditions is not met, e.g, total sales against the number of units sold in a retail shop.
LOOKUP functions were very interesting because of the magic of how easy and efficient it is to search for data in large datasets. HLOOKUP is used mainly to search in a horizontal dataset, VLOOKUP for the vertical dataset, and INDEX is used to search from left to right, e.g, how many units an employee has sold using the formula [INDEX (reference, [row], [column])].
This tool has changed the way I see data; my data before enrollment in this course was chaotic. Now, I can filter data to show what I need, sort with a few clicks(from A-Z), and it's so much easier to keep track of things. I also love the visualisation part, I'm working on perfecting that and hope for the best.
Wish me luck... plumbers!