My initial entry into data analysis was my belief that it would require me to learn a complex programming language or use third party software, before I could begin working with data. My idea was that data analysts would be coding their whole day, using highly specialized tools. Upon starting my Data Science & Analytics journey, however, there was one of the most powerful and widely used tools in data analysis that I knew: Microsoft Excel.
Microsoft Excel is a spreadsheet program designed to enable users to organize, calculate, analyze and visualize data. With the rise of sophisticated analytics tools like SQL, Python, and Power BI, you might wonder why Excel still plays a crucial role in many industries. While these new tools like SQL, Python, and Power BI have created a trend of more advanced data analytics, Excel is still an essential tool for many industries, largely because it is accessible, flexible, and effective for everyday data tasks.
Using Excel in the Real World
Business Decision-Making
There is a lot of data that businesses generate on a daily basis. Businesses can use Excel to keep track of sales, monitor stock levels, compare sales metrics across months and years, and make decisions based on those data.
For instance, a retail outlet can use Excel to compare sales data from one month to the next, and determine what products are selling best during certain seasons. These insights can then be used by the managers to make decisions for inventory and market. Excel can present raw data in meaningful information, which helps us in making decisions based on data.Excel can present the raw data in meaningful information, which helps us make decisions based on data.
Financial Reporting and Budgeting
Excel is the other programme used extensively in finance. It is essential to organizations for budget preparation, tracking of revenue, management of expenses, and financial forecasting.
SUM, SUMIF and SUMIFS are particularly helpful functions. The SUM function totals the values in a range; SUMIF and SUMIFS can total values based on conditions. A business, for instance, can easily determine the company's sales for a specified area or department. These functions help in financial performance analysis and in creating accurate reports.
Marketing and Operational Performance
Excel is a tool that is commonly used by marketing and operations teams for performance evaluations. Marketers can monitor clicks and conversions, advertising spend, and campaign results, and operations can monitor productivity and workflow.
For example, a marketing team could use Excel to compare how well a different social media campaign was going from a performance perspective. They can measure conversion rates and costs to determine which ad campaign provides the highest ROI. Excel can also be used to clean and arrange datasets, making trend analysis much easier.
Formulas and features I have learned to use in Excel.
Data cleaning and validation.
The first thing I learned was clean data. Excel offers tools to remove duplicate data, fix inconsistent data and set up data validation rules. Clean data enhances the accuracy and helps to make decisions based on accurate information.
Sorting and Filtering
Sorting and filtering can help to work with larger data sets. The characteristics enable the user to structure information, prioritize relevant information, and easily identify trends and patterns. Users can quickly narrow down what data fields are important and just look at thousands of rows, rather than reviewing them all individually.
Statistical Functions
I've also picked up some helpful statistical functions:
AVERAGE is a function that returns the average value of a data set.
The middle value of a set of data is determined by using MEDIAN.
The most common value is calculated by MODE.
These functions can provide you with various information regarding the same set of data. For instance, if examining the amount that customers spend, the median spending could give a better idea of the general spending habits of customers while the average might be skewed by some large purchases.
Personal Reflection.
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