How Excel is Used in Real-World Data Analysis

I have began my journey as a beginner in the data analysis field by learning excel. I have previously used excel to store data but never really considered put my mind on how excel is used in the broader perspective of data analysis and the process it takes to collect, organize, validate and process data to extract information.

This journey began with a simple question.

What is Excel?

Excel is an electronic spreadsheet software created by Microsoft. A spreadsheet is an application software used to organize, analyze and present data in an intersecting two-dimensional grid of rows and columns.

Excel has become an industry standard for handling data as it provides a variety of tools and features for data collection, organization, visualization and analysis.

Excel features

Excel provides for one to operate on data through functions/formulas.
A function is a special routine built into the worksheet that enable one to perform complex tasks in a standardized manner.

Form of an excel function

An excel function is composed of four parts:

1. Equal sign (=) - Used to initialize the formula.
2. Function name - It is a descriptive term that identifies the operation to be performed.
3. Parenthesis () - used to contain the function arguments.
4. Arguments - Outlines the range of cells the formula will act on and the conditions to be imposed.

  =Function name(arguments)

Excel functions can be classified into:

Statistical functions
Used to perform statistical computations such as mean, median and mode.

=COUNT(Range)
=COUNTIF(Range, "criteria")
=AVERAGE(Range)
=AVERAGEIF(Criteria range, "criteria", Average range)

Aggregate functions
Used to perform arithmetic, conditional sums and products, exponents and logarithms operations.

=SUM(Sum cell range)
=PRODUCT(Product cell range)
=SQRT(Square root cell range)

Text functions
Used to perform operations on text data.

=LOWER(Range)
=UPPER(Range)
=CLEAN(Range)

Excel as a data analytic tool

After getting a proper understanding of what excel is and how to use it, the next step is to learn how we use these tools to perform data analysis. However, we must begin with knowing what data analysis is.

Data analysis is the process of inspecting, cleaning, transforming and modelling data with the goal of discovering useful information, informing conclusions and supporting decision making in an organization.

Excel is utilized to achieve this in a variety of sectors such as the healthcare, financial, marketing environment, etc. to perform various data analytic operations such as:

Descriptive Analysis
This is analysis that is done to figure out what happened. This is used in the health sector in situations where it is necessary to track the infection rates of communicable diseases in a region region, such as during the covid-19 pandemic where infection records were tracked on a daily basis.

Diagnostic analysis
This is the use of excel functions to go through data to determine why something occurred. This is used in the business sector to outline changes in the business operations, such as changes in the volume of sales, through excel data presentation tools such as charts and graphs.

Predictive Analysis
This involves the use of excel to form projections about the future based on the data. This is used in financial sector to produce possible future investment predictions in a market that is being considered. This is achieved in excel through What-If analysis and Forecast sheets.

Personal reflection

I have spent a week going through excel and learning on how to use it as more than a spreadsheet to hold data. This has led me to discovering the various ways excel provides to engage with data through formulas, sorts, merges and filters to view and produce information for my needs. I have learnt how to validate and clean data so as to ensure data meets the analytic standards.

I believe understanding the use of excel as a data analysis tool is a valuable skill for me as I continue my journey as a data analyst and will provide me with a solid foundation to work with other data tools and platforms in the future.