Using excel to analyze data

Do you want to know how to analyze data in excel?

Are you looking for the best way to analyze data in excel?

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Microsoft Excel is one of the most widely used tools in any industry. While some enjoy playing with pivotal tables and histograms, others limit themselves to simple pie-charts and conditional formatting.

Some may create an artwork out of the dull monochrome Excel, while others may be satisfied with its data analysis. In this discussion, we will make a deep delving analysis of Microsoft Excel and its utility. We will focus on how to analyze data in Excel Analytics, the various tricks, and techniques for it. The discussion will also explore the various ways to analyze data in Excel.

We will discuss the different features of Excel analytics to know how to analyze data in excel (much of which are unexplored to the mass), functions, and best practices.

Our discussion will include, but not be limited to:

(i) Best Way to Analyze Data in Excel

(ii) How to Analyze Sales Data in Excel

(iii) Analyzing Data Sets with Excel

(iv) Data Segregation with Excel

(v) The Importance of Data Reporting

(vi) How to Analyze Data in Excel

How to Analyze Sales Data in Excel: Make Pivot Table your Best Friend

A pivot tool helps us summarize huge amounts of data. One of the best ways to analyze data in excel, it is mostly used to understand and recognize patterns in the data set.

Recognizing patterns in a small dataset is pretty simple. But the enormity of the datasets often calls for additional efforts to find the patterns. In such cases, a pivot table can be a huge advantage as it takes only a few minutes to summarize groups of data using a pivot table.

A data analysis example can be, you have a dataset consisting of regions and number of sales. You may want to know the number of sales based on the regions, which can be used to determine why a region is lacking and how to possibly improve in that area. Using a pivot table, you can create a report in excel within a few minutes and save it for future analysis.

A Pivot Table allows you to summarize data as averages, sums, or counts in Excel from data that is stored in another Spreadsheet, or table. It is great for quickly building reports because you can sort and visualize the data quickly.

Taking a data analysis example like, you may have put together a spreadsheet, which you can copy, and paste into Excel, or use in Google Docs if you would prefer (just click File > Make a Copy).

The spreadsheet contains data with a mock company’s customer purchase information. Since companies purchase at different dates, a pivot table will help us to consolidate this data to allow us to see total buys per company, as well as to compare purchases across companies, for quick analysis.

The Pivot table allows you to take a table with a lot of data in it and rearrange the table so that you only look at only what matters to you.

1. a) Whether you are using a Mac or a PC, you can select the whole dataset that you want to look at and select: “Data” -> “Pivot Table”. When you hit that, a new tab should be opened with a table.

Data Set

1. b) Once you have your table in front of you, you can drag and drop the Column Labels, Row Labels, and Report Filter

• Column Labels go across the top row of your table (for example Date, Month, Company Name)
• Row Labels go across the left-hand side of your table [for example Date, Month, Company Name (same as with column labels, it depends on how you would prefer to look at the data, vertically or horizontally)]
• The Values section is where you put the data you would like calculated (for example Purchases, Revenue)
• Report Filter helps you refine your results. Add anything you would like to Filter by (for example you want to look at Lead Referral Sources, but exclude Google and Direct)

Pivot tables are a great way to manage the data from your reports. You can copy and paste the data into your own Excel file, or create a copy in Google Apps (File > Make a Copy).

How to Analyze Data in Excel:  Analyzing Data Sets with Excel

To know how to analyze data in excel, you can instantly create different types of charts, including line and column charts, or add miniature graphs. You can also apply a table style, create PivotTables, quickly insert totals, and apply conditional formatting. Analyzing large data sets with Excel makes work easier if you follow a few simple rules:

• Select the cells that contain the data you want to analyze.
• Click the Quick Analysis button image button that appears to the bottom right of your selected data (or press CRTL + Q).
• Selected data with Quick Analysis Lens button visible
• In the Quick Analysis gallery, select a tab you want. For example, choose Charts to see your data in a chart.
• Pick an option, or just point to each one to see a preview.
• You might notice that the options you can choose are not always the same. That is often because the options change based on the type of data you have selected in your workbook.

To understand the best way to analyze data in excel, you might want to know which analysis option is suitable for you. Here we offer you a basic overview of some of the best options to choose from.

• Formatting: Formatting lets you highlight parts of your data by adding things like data bars and colors. This lets you quickly see high and low values, among other things.
• Charts: Charts Excel recommends different charts, based on the type of data you have selected. If you do not see the chart you want, click More Charts.
• Totals: Totals let you calculate the numbers in columns and rows. For example, Running Total inserts a total that grows as you add items to your data. Click the little black arrows on the right and left to see additional options.
• Tables: Tables make it easy to filter and sort your data. If you do not see the table style you want, click More.
• Sparklines: Sparklines are like tiny graphs that you can show alongside your data. They provide a quick way to see trends.

Ways to Analyze Data in Excel: Tips and Tricks

It is fun to analyze data in MS Excel if you play it right. Here, we offer some quick hacks so that you know how to analyze data in excel.

• How to Analyze Data in Excel: Data Cleaning

Data Cleaning, one of the very basic excel functions, becomes simpler with a few tips and tricks. You may learn how to use a native Excel feature and how to accomplish the same goal with Power Query. Power Query is a built-in feature in Excel 2016 and an Add-in for Excel 2010/2013. It helps you to extract, transform, and load your data with just a few clicks.

    1. Change the format of numbers from text to numeric

Sometimes when you import data from an external source other than Excel, numbers are imported as text. Excel will alert you by showing a green tooltip in the top-left corner of the cell.

Depending on the number of values in the range, you can quickly convert the values to numbers by clicking on ‘Convert to a number’ within the tooltip options.

However, if you have more than 1000 values, you will have to wait a couple of seconds while Excel finishes the conversion.

You may also convert the values to number format is to use Text-to-Columns using the following steps:

• Select the range with the values to be converted.
• Go to Data > Text to Columns.
• Select Delimited and click Next.
• Uncheck all the checkboxes for delimiters (see below) and click Next.
• Text-Columns-Checkboxes

    2. Select General and click on Finish

When you have lots of numbers to convert this tip will be much faster than waiting for all the numbers to be converted. In Power Query, you just have to right-click on the column header of the column you want to convert.

• Then go to Change Type.
• Then select the type of number you want (such as Decimal or Whole Number)
• Power-Query-Data-Type

How to Analyze Data in Excel: Data Analysis

Data Analysis is simpler and faster with Excel analytics. Here, we offer some tips for work:

• Create auto expandable ranges with Excel tables: One of the most underused features of MS Excel is Excel Tables. Excel Tables have wonderful properties that allow you to work more efficiently. Some of these features include:
• Formula Auto Fill: Once you enter a formula in a table it will be automatically be copied to the rest of the table.
• Auto Expansion: New items typed below or at the right of the table become part of the table.
• Visible headers: Regardless of your position within the table, your headers will always be visible.
• Automatic Total Row: To calculate the total of a row, you just have to select the desired formula.
• Use Excel Tables as part of a formula: Like in dropdown lists, if you have a formula that depends on a Table, when you add new items to the Table, the reference in the formula will be automatically updated.
• Use Excel Tables as a source for a chart: Charts will be updated automatically as well if you use an Excel Table as a source. As you can see, Excel Tables allow you to create data sources that do not have to be updated when new data is included.

How to Analyze Data in Excel: Data Visualization

Quickly visualize trends with sparklines: Sparklines are a visualization feature of MS Excel that allows you to quickly visualize the overall trend of a set of values. Sparklines are mini-graphs located inside of cells. You may want to visualize the overall trend of monthly sales by a group of salesmen.

To create the sparklines, follow these steps below:

1. Select the range that contains the data that you will plot (This step is recommended but not required, you can select the data range later).
2. Go to Insert > Sparklines > Select the type of sparkline you want (Line, Column, or Win/Loss). For this specific example, I will choose Lines.
3. Click on the range selection button Select Range Excel Button to browse for the location of the sparklines, press Enter and click OK. Make sure you select a location that is proportional to the data source. For example, if the data source range contains 6 rows then the location of the sparkline must contain 6 rows.

To format the sparkline you may try the following:

To change the colour of markers:

1. Click on any cell within the sparkline to show the Sparkline Tools menu.
2. In the Sparkline tools menu, go to Marker Color and change the colour for the specific markers you want.

For example High points on the green, Low points on red, and the remaining in blue.

To change the width of the lines:

1. Click on any cell within the sparkline to show the Sparkline Tools menu.
2. In the Sparkline tools contextual menu, go to Sparkline Color > Weight and change the width of the line as you desire.

Save Time with Quick Analysis: One of the major improvements introduced back in Excel 2013 was the Quick Analysis feature. This feature allows you to quickly create graphs, sparklines, PivotTables, PivotCharts, and summary functions by just clicking on a button.

When you select data in Excel 2013 or later, you will see the Quick Analysis button Quick Analysis Excel Button in the bottom-right corner of the range selected. If you click on the Quick Analysis button you will see the following options:

• Formatting
• Charts
• Totals
• Tables
• Sparklines

When you click on any of the options, Excel will show a preview of the possible results you could obtain given the data you selected.

• If you click on the Quick Analysis button and go to charts, you could quickly create the graph below just by clicking a button.
• If you go to Totals, you can quickly insert a row with the average for each column:
• If you click on Sparklines, you can quickly insert Sparklines:
• As you can see, the Quick Analysis feature really allows you to quickly perform different visualizations and analysis with almost no effort.

How to Analyze Data in Excel: Data reporting

Data reporting in Excel analytics requires more than just accounting skills, it also requires a thorough knowledge of excel functionalities and the ability to add beauty to your report.

• Turn Auto Refresh off before editing the Excel workbook. This will stop the table from refreshing when you are making changes on the worksheet. To do this, click on the Refresh icon at the bottom of the Excel Report Designer Task Pane and then select “Switch auto-refresh off”.
• When adding a new row to the layout, select a cell in the table area below where you want to insert the new row. Then right-click and from the context menu select Insert > Table Rows Above.
• When deleting columns or rows make sure you use the Table Delete functions similar to the Insert functions above. To remove a column or row, select a cell in the table area of the row or column you want to remove.  Then right-click and from the context menu select Delete and then either Table Columns or Table Rows.
• Remove unneeded rows or columns from the table. Having fewer cells in the layout makes it easier for the table to refresh, so removing any unneeded ones will improve performance.

Excel has several other uses that may not have been covered here. Play around with visualize complex data or organize disparate numbers, to discover the infinite variety of functions in Excel analytics. Strong knowledge of excel is a boon if you are looking forward to a career in data analytics.

This was all about how to analyze data in excel, how to analyze sales data in excel along with a few data analysis example.

Hopefully, you must have understood the best way to analyze data in excel.

We offer one of the best-known courses in Data Analytics Using Excel Course. The course enables you to learn tools such as Advanced Excel, PowerBI, and SQL.  The live projects and intensive training program also empower you to come up with solutions for real-life problems.

In the world of technology, data is how machines communicate. It’s a language of numbers and metrics; a simple, yet hauntingly complicated system that gives us non-machines many headaches.

Microsoft Excel helps us break this language barrier and turn raw numbers into ideas, trends and insights.

Analyzing data in Excel is also useful when you need to transform your data into charts and other visuals. These are invaluable tools that help you see the story behind the numbers and highlight your best assets and most significant shifts in reports to clients and stakeholders.

When it comes to creating effective charts for your data, seeing is really believing. Very few managers have the time to analyze data with Excel by hand. Charts make the insights jump off the screen.

This discussion will look at how analysts, researchers, and managers can use Excel to transform their data into helpful charts and stunning visuals.  It is the most effective way to detect trends, patterns, outliers, and other notable events in your data sets. In this blog you will learn:

• How To Analyze Data in Excel?
• How to Use ChartExpo Add-in for Data Analysis in Excel ?
• An Overview Of Excel
• How to Carry Out the Data Analysis Process?
• What is the Importance of Data Analysis for your Business?
• How does Excel Help Digital Marketers in Data Analysis?

How To Analyze Data in Excel?

Navigating through data can feel like a nightmare. It can be quite tricky to explore and process data when dealing with large chunks of it all at once.

After all, not all data is useful or relevant. To make matters worse, data in its raw form can often cause more confusion than clarity.

Before you can derive any sort of actionable intelligence from your data, it needs to be gathered, filtered, cleaned, visualized, analyzed, and reported. All of these steps form the data analysis process.

The data analysis process can be different each time you perform it. Unique obstacles and challenges can arise that make conclusions difficult to obtain. Thus, it is best when you have dynamic solutions to handle all of the unexpected bumps in the road.

Excel’s robust toolset offers an excellent kick-start to the process. Not only is it a convenient way to collect, arrange and organize data, but you can also perform complex computations and visualize the data with some basic charting options.

How to analyze data in Excel? From your spreadsheet data, you may even be able to glean some basic insights. In other words, you can perform some rudimentary analysis right from your spreadsheets, before charting or digging deeper into the numbers.

How to Use ChartExpo Add-in for Data Analysis in Excel ?

Excel has a lot of benefits to business owners and marketers. It is a convenient tool for collecting and organizing data. However, it does have its limitations. One of these deficiencies is in charting. Excel only offers a small handful of charts for marketers to use.

As we’ve covered, being able to display data as a chart is extremely valuable. It can save you hours when it comes to detecting insights and understanding the story behind the raw numbers.

So how do you get the most out of your data with this lack of charting options? With the ChartExpo add-in for Excel, you can gain new functionality from Excel.

ChartExpo adds over 80 different Excel visualizations. Many of these charts are designed specifically for digital marketers and PPC advertisers.

Manually analyzing data requires a lot of surfing through spreadsheets. You may even need to have some coding abilities. ChartExpo for Excel makes it simple to gain insights from even a complex spreadsheet.

To get started with the ChartExpo add-in:

• Open your Excel application.
• Open your spreadsheet and click INSERT from the top toolbar. From the drop-down menu, you will see My Apps.
• Click on My Apps and then click to See All.

• If you’ve already added ChartExpo for Excel, you’ll see it available. Otherwise, you’ll have to visit the Microsoft Office Store and download the free plugin.
• Once you’ve installed ChartExpo, select the add-in and click on the Insert button.

• By clicking insert, you’ll add ChartExpo to your Excel environment.
• You’ll be asked to log in with your Microsoft account. If you don’t have one, you can create one for free.
• It’s worth mentioning that you are only required to log into your Microsoft Account the first time you access ChartExpo. Each time you use the plugin after, you will not have to undergo this step.

• At this stage, you are ready to begin using ChartExpo. You have access to the entire library of charts and visualizations. Click on the start button to continue.

• Click Create Chart to get started.

• Next, you’ll see a list of different chart categories. You can select any group to expand it and see the individual charts available under that category.

Let’s say you are running a Google Ads campaign and you want to analyze your ad impressions by time. You can select the Pay-per-click (PPC) category and then choose the Dayparting Chart.

• Once you create the chart, you’ll see a sample Dayparting chart that looks like this:

• By clicking Explore Sample Data, the data will be automatically added to your spreadsheet.

• You can change the data in this table to reflect your campaigns’ data. After adding your own data, click on the Create Chart From Sheet Data Option

• This will change the Dayparting chart to reflect your own data.

With this PPC chart, you can see what days of the week and hours of the day generate the highest impressions. Dark squares reflect times when impressions are at their highest, while lighter squares are times that perform poorly for impressions.

You can use these insights to:

• Stretch your campaign budget: You can change when and how often your ads appear in order to take advantage of this Dayparting schedule. This can help you stretch your budget to its limits by only showing ads at high-value times.
• Maximize your impressions: Impressions can reflect times when your target audience is most active. By increasing bids at these times, you can improve the likelihood that your ads are shown during peak times.
• Time your strategies: Your Dayparting data can also be used to inform your other strategies. When your ads are seeing lots of activity, it could mean valuable times for your social posts, content updates and other tactics.

Remember, if you face any issues with ChartExpo library in Excel 2013, make sure to install office service pack 1 on Windows.

An Overview Of Excel

Excel is a software tool developed by Microsoft with the core function of making spreadsheets. However, the application can do much more than just make spreadsheets.

There is a vast selection of tools, settings and other options. No matter how you want to present or organize your data, there are options available to help you.

This selection includes pivot tables, a macro programming language (called Visual Basic for Applications or VBA), powerful calculation capabilities and much more.

As part of the Microsoft Office Suite, Excel is compatible with every major operating system — Windows, macOS, Android, iOS — and some lesser-known ones.

Most users have Excel Basic, the standard application. There are other, more expensive options, which have even greater capabilities.

Over the years, Excel has become the go-to method for organizing and presenting data because of its smooth, practical and flexible interface.

You’d be hard-pressed to find a business today that doesn’t use Excel to some degree, mostly because of how integral data management has become for all types of companies.

The reason that Excel is so popular is because of how many different ways it can be used. Even if you aren’t a master of VBA or know how to set up complex computations in your spreadsheets, you can still get a lot of use from this program.

It is truly a vital, versatile and powerful tool for all types of data.

How to Carry Out the Data Analysis Process?

To extract the most value from your data, you need to consider how data analysis actually works. Here is an overview of the step-by-step process to analyze data with Excel.

1. Specifying Data Requirements

To perform effective data analysis, you need to set the requirements of the data. This means establishing the structure and categories of the data that will be pertinent to your analysis.

For example, if you analyze your marketing audience, your data requirements may include things like their age, income, location, etc. These requirements will dictate what data needs to be collected.

2. Data Collection

Once you have defined the variables and organized them into categories, you need to collect all of the relevant data related to these areas. Your data needs to be complete and as accurate as possible.

Ultimately, it is up to you to source your data correctly and ensure its relevance, quality and accuracy. The information still needs to be filtered and cleaned.

3. Data Processing

After you collect the raw data, you need to organize it for further analysis. You must structure the data into proper categories. This is the stage when you need to enter the data into a spreadsheet or develop some type of data model to arrange the information logically.

Organizing the data in this fashion makes it possible to filter and clean the data.

4. Data Cleaning

The data you have organized may look nice and neat, but it is likely incomplete and may contain errors or duplicate items. Data cleaning is the process of reviewing your collected data and fixing any errors or inaccuracies you may find.

The cleaning process will depend on the type of data you’ve gathered. For example, if it is financial data, you can simply sum up totals and make sure they match your records. This is a pre-review step that is important for establishing the truth and reliability of your data points.

5. Data Analysis

Once your data passes through all of the phases above, it is ready for analysis.

You can manually perform the data analysis process by physically examining each row and column of data and comparing the totals and recognizing patterns and other correlations. If your data set is extensive, this is extremely challenging and can border on the impossible.

That is where data visualization tools come into play. By charting the data, you can visually see the patterns, outliers, trends, etc. It is an extremely quick method for gaining a deeper understanding of your data.

6. Communication

While the analysis of the data may seem like the final step, you still need to be able to share and communicate your findings. You may need to report your data insights to stakeholders, clients, team members or other parties.

Whoever is reading your data needs to be able to reach and understand the same conclusions. Sometimes, the data may be too complex and difficult to explain without the help of charts and other tools to simplify the information and communicate the findings effectively.

What is the Importance of Data Analysis for your Business?

When running a business, or even just managing a Google Ads account, it is often difficult to know where to start, where to go and the best way to get there. The Digital Age has produced so many new audiences, channels, strategies and other options that are worth exploring.

Our world has become so data-driven. It is crucial to be able to make sense of your marketing data, no matter what type of business you operate.

Hidden in this data is everything you need to learn how to reach your target audiences, make better products, construct stronger ad messages, increase your marketing ROI and so much more.

The problem is that all of this data is a jumbled mess of numbers coming from all different sources. It’s a massive, tangled ball of string (attached to several other equally-tangled balls of string).

Data analysis unravels this mess and reveals the insights obscured by the chaos.

While every path is valuable, some are more fruitful than others. The importance of data analysis is discovering the most promising course of action.

You identify your best and worst performers and use this information to optimize your strategies and maximize your returns.

How does Excel Help Digital Marketers in Data Analysis?

Sales is a numbers game and, thanks to the Internet, marketers have more numbers than ever to deal with. This is why data has become so crucial in the Digital Age. However, it is important to realize that data is not valuable unless you can analyze it and extract insights.

These insights are what make Excel and data so helpful to digital marketers. Digital marketers can use Excel to develop and track different strategies that generate new customers.

Here are all of the ways that Excel and data analysis are helpful to digital marketers.

• Budgeting

Before you do anything in your digital marketing, you have to answer the budgeting questions. How much money can you afford to spend on each strategy? Think about your entire budget. How much do you allocate towards paying writers for SEO content assets? How high will you set your budget for PPC and Google Ads?

An Excel spreadsheet can quickly arrange your cost-related data and show where and how your budget is utilized. You can save a lot of time by using Excel to track your costs. By having all of your expenses in one place, it is easier to measure how your money is being spent and whether the returns are worth it.

After all, it’s not just about what you are spending, but also what you are getting in return. A pillar of successful digital marketing is being able to optimize how you spend your budget to achieve the best possible results.

• Maintain a Blog Calendar

It is important to your customers that you keep in contact with them regularly. You want to avoid long lapses in content or sudden bursts of posting.

Using an Excel spreadsheet, you can easily build an editorial calendar, which will be extremely useful for scheduling the writing and uploading of web content for your pages. It is easier for most people to stay on track when they have a calendar to work from.

Keeping all of your information in the same space makes it easier for you to keep it connected and stay on track. Many teams use Excel spreadsheets to delegate tasks and decide who will do what, when and where.

• Tracking SEO Results

Tracking SEO keywords is vital to successful organic search marketing. There are many keyword research and analysis tools that will help you select better search targets and track their performance.

With an Excel spreadsheet, you can take this data and easily compare different keywords. You can also track costs and measure the ROI of each prospective keyword target.

At the end of the day, there is no better way than Excel to collect, organize, track and save data regarding keywords and costs.

• Maintain Social Content

Social media is a mandatory strategy for building and cultivating your audience. Similar to having a blog calendar, you can also use Excel to schedule and organize your Tweets, Facebook posts, Instagram Stories, LinkedIn discussions, etc.

More importantly, you can collect your social media metrics across these various platforms and organize them into a single spreadsheet. This allows you to have full visibility of how each platform performs and contributes to your overall social media marketing strategy.

You can use this data to determine which social media platforms are providing the best results, as well as what types of posts work best on which site. If you also track when each post is published, you can use this spreadsheet to determine the best times and days to publish posts.

• Tracking Google Ads

Google provides many ways for you to track how effectively your ads are working for you and how many clicks and conversions the ads are generating. Excel is, once again, helpful in collecting and organizing these various metrics.

A common way that PPC marketers use Excel is to set up a table of costs versus clicks. This simple analysis can provide a baseline of your costs versus returns. From there, you can dig deeper into conversions and the actual revenue created from these clicks.

After all, just because you’ve generated lots of clicks doesn’t necessarily mean that your strategies are profitable. Excel can help you determine what ad messages are actually producing profits in your PPC campaigns.

• Generate and Track Leads

You can create a traffic/lead tracker with Excel to monitor how many website visitors took that next step and expressed interest. This could be clicking through to your website, subscribing to a newsletter, etc.

Lead generation is a huge part of sales. Excel can help you organize each lead based on their position in your funnel. By analyzing how much of your traffic is developing into viable leads, you can determine whether you’re wasting money or not on your prospects.

In other words, making spreadsheets can help you assess what is working for your business and what isn’t.

• Monthly Market Metrics Reports

Seeing your marketing efforts payoff is one of the most rewarding feelings. With an Excel spreadsheet, you can keep track of all of your investments and returns in one place. This will keep your costs in check and ensure that each strategy you implement helps your business.

Excel can help you perform a “monthly marketing metric report.” This simple spreadsheet will show your key metrics month-to-month. Sometimes, strategies change. What worked last month is not guaranteed to achieve the same returns this month.

Tracking this data monthly will ensure that you are always on top of any significant changes in your marketing data.

FAQs:

What is the best way to analyze data in Excel?

Excel is not only for tabular data, tabular data analysis becomes difficult if there are many rows and columns. Best way to analyze data in Excel is through visualizations.

What is the data analysis tool in Excel?

ChartExpo add-in is to visualize your data with better insights. You can use this as a tool in Excel to give your data analysis a new angle for improved understanding.

How do you analyze large data in Excel?

You can use quick analysis tool in excel for larger data sets but if you convert your data to awesome visualization , it will become much easier to analyze large datasets. ChartExpo library have wonderful visualization collection for almost all types of large dataset analysis.

Wrap Up

Unfortunately, data and numbers are so much more complicated than they ever have been in the past. Excel helps you collect, organize and manage the complexities of your data.

Hands down, it is one of the most important tools for a data analyst and for digital marketer who want to visualize their data in better way.

That said, there are some limitations when using Excel, particularly when it comes to charting options.

This is where ChartExpo becomes exceptionally valuable to marketers and pay-per-click advertisers. By adding over 80 different charts and visualization options, you have a lot more freedom with presenting your data.

When you select the perfect chart to visualize your data, it makes discovering valuable insights and reporting results so much easier.

If you are already analyzing data with Excel, you can improve your efforts with just one click by downloading the ChartExpo add-in.

Explore the 30 most popular pages in this section. Below you can find a description of each page. Happy learning!

1 Find Duplicates: This example teaches you how to find duplicate values (or triplicates) and how to find duplicate rows in Excel.

2 Histogram: This example teaches you how to make a histogram in Excel.

3 Regression: This example teaches you how to run a linear regression analysis in Excel and how to interpret the Summary Output.

4 Pareto Chart: A Pareto chart combines a column chart and a line graph. The Pareto principle states that, for many events, roughly 80% of the effects come from 20% of the causes.

5 Remove Duplicates: This example teaches you how to remove duplicates in Excel.

6 Gantt Chart: Excel does not offer Gantt as chart type, but it’s easy to create a Gantt chart by customizing the stacked bar chart type.

7 Line Chart: Line charts are used to display trends over time. Use a line chart if you have text labels, dates or a few numeric labels on the horizontal axis.

8 Correlation: We can use the CORREL function or the Analysis Toolpak add-in in Excel to find the correlation coefficient between two variables.

9 Pie Chart: Pie charts are used to display the contribution of each value (slice) to a total (pie). Pie charts always use one data series.

10 Data Tables: Instead of creating different scenarios, you can create a data table to quickly try out different values for formulas. You can create a one variable data table or a two variable data table.

11 t-Test: This example teaches you how to perform a t-Test in Excel. The t-Test is used to test the null hypothesis that the means of two populations are equal.

12 Advanced Filter: This example teaches you how to apply an advanced filter in Excel to only display records that meet complex criteria.

13 Frequency Distribution: Did you know that you can use pivot tables to easily create a frequency distribution in Excel? You can also use the Analysis Toolpak to create a histogram.

14 Scatter Plot: Use a scatter plot (XY chart) to show scientific XY data. Scatter plots are often used to find out if there’s a relationship between variable X and Y.

15 Anova: This example teaches you how to perform a single factor ANOVA (analysis of variance) in Excel. A single factor or one-way ANOVA is used to test the null hypothesis that the means of several populations are all equal.

16 Compare Two Lists: This example describes how to compare two lists using conditional formatting.

17 Bar Chart: A bar chart is the horizontal version of a column chart. Use a bar chart if you have large text labels.

18 Goal Seek: If you know the result you want from a formula, use Goal Seek in Excel to find the input value that produces this formula result.

19 Box and Whisker Plot: This example teaches you how to create a box and whisker plot in Excel. A box and whisker plot shows the minimum value, first quartile, median, third quartile and maximum value of a data set.

20 Shade Alternate Rows: This example shows you how to use conditional formatting to shade alternate rows.

21 Quick Analysis: Use the Quick Analysis tool in Excel to quickly analyze your data. Quickly calculate totals, quickly insert tables, quickly apply conditional formatting and more.

22 Sparklines: Sparklines in Excel are graphs that fit in one cell. Sparklines are great for displaying trends. Excel offers three sparkline types: Line, Column and Win/Loss.

23 Slicers: Use slicers in Excel to quickly and easily filter pivot tables. Connect multiple slicers to multiple pivot tables to create awesome reports.

24 Trendline: This example teaches you how to add a trendline to a chart in Excel.

25 Pivot Chart: A pivot chart is the visual representation of a pivot table in Excel. Pivot charts and pivot tables are connected with each other.

26 Subtotal: Use the SUBTOTAL function in Excel instead of SUM, COUNT, MAX, etc. to ignore rows hidden by a filter or to ignore manually hidden rows.

27 Combination Chart: A combination chart is a chart that combines two or more chart types in a single chart.

28 Randomize List: This article teaches you how to randomize (shuffle) a list in Excel.

29 Unique Values: To find unique values in Excel, use the Advanced Filter. You can extract unique values or filter for unique values.

30 Icon Sets: Icon Sets in Excel make it very easy to visualize values in a range of cells. Each icon represents a range of values.

Check out all 300 examples.

Excel is currently the most flexible tool used in business. It has been around since the 1980s and continues to be the most essential data structure and analysis tool. It is an indispensable resource for personnel in IT, Finance, HR, Marketing, and virtually every other department imaginable. Let us have a conversation about its usefulness for our esteemed marketers.

Excel was used as a tool for data storage and organization. Over time, it became a tool for doing modest data calculations. Today, after several upgrades, it is recognized as a gateway into the realm of analytics. Let us accept the strength of this instrument and plunge into the realm of Excel-based marketing analytics with this post. This article will help to demonstrate the power of Excel in data analytics.

What does Excel do?

It is true that huge organizations have abandoned spreadsheets for enormous data sets, yet spreadsheets are still utilized for everyday tasks. In its most fundamental form, each cell in Excel contains data points. To facilitate viewing and organizing, exports of raw data, sales dates, SKUs, and units sold are inserted (or imported) into a spreadsheet. An effective Excel spreadsheet will arrange unstructured data into a format that makes it simpler to extract insights that can be put into action. Excel allows you to define fields and functions that perform computations with more sophisticated data. Even with bigger data sets, segmented data may be examined and viewed more thoroughly without the need for additional tools. Determine hypothetical profit margins or budgets for departments. While it cannot create a complete data product on its own, it may provide easy-to-read graphics and precise computations.  If you are considering a career as an analyst or need to work with data to create a report, analytics is not the simplest procedure to learn in a single sitting. Use data spreadsheets as a little representation of a bigger data endeavor.

• What is the intent? Overview? What insights do you require?
• Where does the data originate? What exports and imports are required?
• Does the data require translation?
• What obstacles exist? Limitations?

How do you get your conclusions? Which post-analysis choices must be made?

Excel is an excellent starting point for context, but a true big data project requires far more people, expertise, and degree of detail.

What benefits does Data Analysis provide for Sales and Marketing?

Information Analysis will provide additional insights used to boost advertising activities. Be it their budgetary allocations, their interest group, or geology. Let us consider the following scenario: a marketing administrator is arranging a paid assignment on Google. Based on keyword trends, reverberation rates on the landing page, and the number of leads that will be generated from these clicks, he will have a good idea of how many clicks the promotion will generate within a certain time frame. An exhaustive data analysis will reveal the average income/benefits that will be generated by this project, enabling him to easily determine ROI, adjust advertising budgets as necessary, and establish benchmarks for each project.

How to Conduct Data Analysis in Microsoft Excel

Let us discuss the well-known features and functions of Microsoft Excel that are commonly employed by business professionals for data analysis in Excel.

Turn Tables

Turn tables allow you to extract relevant information from a massive dataset. This is considered the most effective method for analyzing information. You may embed a Pivot Table and then move fields, sort, filter, or modify the summary calculation. You may also create a Two-Layer Pivot Table. Group Pivot Table Items, Multi-level Pivot Table, Frequency Distribution, Pivot Chart, Slicers, Update Pivot Table, Calculated Field/Item, and Get-Pivot-Data are useful capabilities.

What-if Evaluation

Consider the possibility that Analysis facilitates the exploration of many routes pertaining to a variety of scenarios involving values or equations. Excel’s What-if analysis is initiated by clicking on the What-if button. After entering details about the anticipated circumstance, click the Outline button. Under this capability, you may also explore Data Tables, Quadratic Equation, and Goal Seek.

Limiting Formatting

The Conditional Formatting feature lets highlight cells with a distinct color based on the value assigned to it. Contingent planning is useful for managing rules, information bars, color scales, symbol sets, observe copies, concealing substitute columns, examining two documents, conflicting rules, the agenda, and Marketing Professionals.

Diagrams

A chart is more useful than a sheet since it displays information in several ways and is extremely easy to create. You can create an outline, alter the graph type, adjust the line or segment, legend location, and information markings. Column Chart, Line Chart, Pie Chart, Bar Chart, Area Chart, Scatter Plot, Data Series, Axes, Chart Sheet Trendline, Error Bars, Sparklines, Combination Chart, Gauge Chart, Thermometer Chart, Gantt Chart, and Pareto Chart are some of the many types of outlines in Microsoft Excel.

Sort and Filter

Sorting and filtering are the most frequently used Excel functions. Within segments, it should be able to arrange in ascending or descending order. List arrangement should be feasible via shading, inversion, or randomization. Channels are utilized to display information that conforms to models. Number and Text Filters, Date Filters, an Advanced Filter, a Data Form, Remove Duplicates, Outlining Data, and Subtotal are all available.

Vlookup and Hlookup

Examiners rely on Vlookup and Hlookup to notice a value in a data collection and get other attributes linked to it. It is frequently used by information analysts to connect and consolidate vital data from several dominant Marketing Professionals.

Can Excel be Used for Complex Data Analysis?

Excel has the capability to do predictive analytics using plugins. For complex data analysis, the add-ons in Excel will centralize all your complex business formulas and calculations from multiple systems in one sheet, view, or graph. Having all your data in one centralized place and detailed, customizable dashboards enable you to easily compare, measure, and analyze complex data so that you can make informed business decisions.

A company may sell its products and services in multiple countries. It uses eCommerce platforms for its Online Stores. They have different marketing platforms, payment gateways, inventories, logistic channels, and target audiences in each country. Hence, businesses are bound to use several tools and applications for each job to be done.

For a simple calculation of profit, where

Profits/Losses = Sales – Expenses

The sales data will come from eCommerce sites, Expenses from the marketing costs on the platforms like Google AdWords, and Facebook Ads. There can be other expenses like purchasing stock which might come from inventory management platforms like Olabi, which further need to be added to all other expenses occurred that is usually present in accounting software like FreshBooks. Additionally, there will be different data silos for each country. Thus, you must pull all these data from multiple platforms for each country separately in Excel, and then analyze all this data together with the expense data and calculate profits. It involves a lot of working hours which cost money, and there is usually a time lag involved, which reduces the accuracy of the analysis and its effectiveness as the data is not analyzed in real-time. Thus, it becomes necessary to consolidate all the data in a data warehouse using a data pipeline.

Daton is a modern cloud data pipeline designed to replicate data to a cloud data warehouse with the utmost ease. Daton, our eCommerce-focused data pipeline, has built-in support for more than 100 applications, databases, files, cloud storage, analytics, CRM, Customer support, and many others. Analysts can replicate data from any source to any destination (BigQuery, Snowflake, Redshift), without writing a single line of code and in a matter of minutes.