The type of data that analysts have to deal with can range from simple sales and inventory to something as sophisticated as scientific and social statistics. Thus, it’s essential for them to identify the right tools to use for the field they’re working on.
Among the choice of data analytics tools, Excel is one of the favorites. Aside from being accessible and versatile, there are also plenty of Excel templates that analysts can utilize for added efficiency and convenience. This basic Microsoft Office program can be a powerful ally in analyzing data across various fields if you know the right tricks and formulas to use.
Basic Excel Functions for Data Analysis
CONCATENATE is one of the most useful and powerful formulas for analyzing data thru Excel. It combines data from multiple cells into one cell, which comes handy when creating API endpoints, product SKUs, etc.
The formula for CONCATENATE is: =CONCATENATE(select/enter the cells you want to combine)
Entering the formula for LEN will show you the total number of characters within a given cell. It’s useful when determining differences between lengthy entries or sequences like Unique Identifiers or what’s commonly known as UIDs.
The formula for LEN is: =LEN(select/enter cell)
The COUNTA formula is of significant use whenever you come across incomplete data sets, which will happen pretty often. COUNTA makes evaluating gaps in the data set more convenient as you won’t have to reorganize the data anymore.
The formula for COUNTA is: =COUNTA(select/enter cell)
As a data analyst, SUMIFS should be one first formula you need to know and learn about. Even non-analysts are familiar with the basic formula =SUM for adding a set of values. SUMIFS, on the other hand, makes it easier to get the sum of values even if they are not of the same criteria.
A variation to the SUMIFS formula is AVERAGEIFS which allows you to get the average of a set of values based on multiple criteria.
The formula for SUMIFS is: =SUMIF(range,criteria) or =SUMIF(range,criteria[sum_range])
The formula for AVERAGEIFS is: =AVERAGEIF(select/enter cell,criteria[average_range]) or =AVERAGEIF(select/enter cell,criteria)
Perhaps one of the most widely-used data analysis function in Excel, VLOOKUP helps you search for values in the table and then “marry” the data together to get a corresponding value.
The formula for VLOOKUP is: =VLOOKUP(lookup_value,table_array,col_index_num, [range_lookup])
The IF ERROR function is something that you should take advantage of. Sometimes, you don’t get a match when searching for values in a dataset, which prompts the #VALUE error. In such cases, you can use the IF ERROR formula to replace #VALUE errors in the datasheet with any text or value.
The formula for IF ERROR is: =IFERROR(find“value”,select cell,value_if_error)
If you want to check how many times a dataset meets specific criteria, COUNTIFS is the formula to use. Data analysts consider this as a very powerful formula because of its capability to return results for a limitless number of criteria.
The formula for COUNTIFS is:
Considered a “data analysis gold,” SUMPRODUCT is your go-to function for calculating the average returns and price points in a dataset. This function works by multiplying a range of value by their corresponding counterparts.
Using Excel to Generate Inference from Data
Creating charts and graphs is one of the simplest yet most effective ways to make deductions using gathered data. Building a chart on Excel is pretty straightforward; you just have to select the range of data you’d like to chart and then press F11, which creates a chart on a new page. If you wish to have your chart on the same worksheet as your data, press ALT + F1 instead.
The resulting chart will be in the default format, but you can customize its design and contents to your desires.
Pivot tables allow you to generate inferences from datasets almost effortlessly. Think of it as a summary sheet that lets you add, total, average, and perform a variety of operations according to your selected reference feature. It is especially useful when making data-based decisions.
To create a Pivot Table, drag over the list of data, choose the Insert tab and select the Pivot table. A Pivot Table field list panel will appear, and all you have to do is arrange/place the items on the list inside the boxes at the bottom of the board. The diagram on the left side is your Pivot Table.
Excel – The Best Data Analysis Tool for Beginners
Anybody to wishes to dabble or pursue a career in data analysis should spend time familiarizing themselves with Excel. It’s the perfect starting point for freelancers and startups with its numerous tools and applications. Compared to other software out there, it’s by far the easiest to learn and the most affordable.
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