If you’ve ever used Excel, you’ve likely felt the agony of selecting the wrong formula to analyze a batch of data. It’s possible that you spent hours working on it before giving up because the data output was inaccurate or the function was too complex; it seemed simpler to manually count the data. This top 15 list for data analysis in Excel is for you if it describes you.
Excel has hundreds of functions, so trying to match the proper formula with the right type of data analysis can be overwhelming. The most beneficial features don’t necessarily need to be complex. Your capacity to examine data will be improve by fifteen straightforward routines, and you’ll wonder how you ever managed without them.
There is a function in this list for everyone, regardless of your level of Excel proficiency or how frequently you use it at work.
One of the simplest to understand but most effective formulas for data analysis is =CONCATENATE (Wann, 2020). Combine information from numerous cells, including text, numbers, dates, and more. This is a great method for generating Java queries, product SKUs, and API endpoints.
=CONCATENATE(SELECT CELLS YOU WANT TO COMBINE)
The fast count of characters in a cell is provided by =LEN. By utilizing the =LEN formula to determine how many characters are present in the cell, you can distinguish between two different types of product Stock Keeping Units (SKUs). LEN is particularly helpful when attempting to distinguish between several Unique Identifiers (UIDs), which are frequently lengthy and not in the proper order.
=COUNTA determines whether or not a cell is empty. Every day, as a data analyst, you will encounter incomplete data sets. You may assess any gaps in the dataset using COUNTA without having to rearrange the data.
=DAYS means what it says. The number of calendar days between two dates is calculate using this function. It is a helpful tool for determining the lifespan of items, contracts, and run-rating revenue based on service duration—a vital data analysis step.
=NETWORKDAYS is a little more reliable and practical. The number of “workdays” between two dates can be calculate using this formula, which also has a provision for accounting for holidays. Even workaholics occasionally require a break! Comparing time frames using these two formulas is extremely useful for project management.
=DAYS(SELECT CELL, SELECT CELL)
=NETWORKDAYS(SELECT CELL, SELECT CELL,[numberofholidays])
note: [numberofholidays] is optional
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=One “must-know” formula for a data analyst is SUMIFS. However, what if you need to total numbers based on many criteria? The typical way is =SUM. It is SUMIFS. To evaluate how much each product contributes to top-line income.
note: [sum_range] is optional
AVERAGEIFS offers the same ability to take an average based on one or more criteria as SUMIFS.
=AVERAGEIF(SELECT CELL, CRITERIA,[AVERAGE_RANGE])
note: [average_range] is optional
One of the most practical and well-known data analysis functions is VLOOKUP. You’ll probably need to “marry” data together as an Excel user at some point. For instance, accounts receivable may be aware of the price of each product, but shipping can simply supply units shipped. That is the ideal use for VLOOKUP.
The price table and reference data (A2) use to have Excel search for matching terms in the first column and provide an adjacent value.
Powerful tools like =FIND and =SEARCH can be used to isolate particular text within a data source. Both are listed here because =FIND returns a case-sensitive match, thus if you ask for “Big” using FIND, you will only get results for Big=true. However, a =SEARCH for “Big” will match with Big or big, broadening the search. This is especially helpful when searching for abnormalities or distinctive identifiers.
=FIND(TEXT,WITHIN_TEXT,[START_NUMBER]) OR =SEARCH(TEXT,WITHIN_TEXT,[START_NUMBER])
Note: [start number] serves as a starting cell for the search in the text and is optional.
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Any analyst who actively presents data should take advantage of =IFERROR. Using the preceding illustration, searching a dataset for particular words or values won’t produce a match. While not harmful, that results in a #VALUE mistake, which is distracting and ugly.
To replace the #VALUE errors with any text or value, use =IFERROR.
The simplest method to determine how many times a dataset satisfies a set of requirements is to use =COUNTIFS. Because you may enter virtually any criteria, COUNTIFS is extremely powerful.
The efficient and simple techniques =LEFT and =RIGHT can be used to extract static data from cells. While =RIGHT returns the “x” number of characters from the cell’s end, =LEFT returns the “x” number of characters from the cell’s beginning.
Despite being an outdated Excel function, =RANK is still useful for data analysis. You may rapidly indicate the order of values in a dataset by using the =RANK function. The sample uses RANK to identify the clients who place the most product orders.
note: [order] is optional
Unlike the min function, which just allows you to take the minimum of a set of values, =MINIFS also allows you to match on criteria.
Like its sibling minifs, MAXIFS also allows you to match on criteria, but this time it searches for the greatest number.
The function =SUMPRODUCT is a great tool for figuring out typical returns, price points, and margins. SUMPRODUCT multiplies one set of values by the values in the corresponding rows. It’s pure data analysis gold.
We sincerely hope that was helpful. Take a look at the Excel course that has helped hundreds of thousands of people grasp Excel if you’re interested in learning more about data analysis in Excel.
BAW (2022). How Academic Help Providers Save the Students’ Future?. https://bestassignmentwriter.co.uk/blog/how-academic-help-providers-save-the-students-future/
James Wann (2020). Excel Data Analysis Functions You Need to Know. https://excelwithbusiness.com/blogs/news/15-excel-data-analysis-functions-need
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