Building Heat Map Google Sheets: 2 Easy Steps

The amount of data generated every day is a staggering 2.5 quintillion bytes. With such vast data at our disposal, it is important to understand how to leverage it to garner actionable insights for your business growth. Data-driven decisions made by organizations can streamline their business processes, offer personalized services to customers, yield better revenue, and more. However, while organizations are awash with data and proficient at deriving value out of it, the insights are futile if they are not presented in a digestible and understandable manner.

The problem is directly addressed by Data Visualization tools, which create static or moving visuals to communicate observations in a way that words and statistics alone cannot. Another reason to opt for Data Visualization tools for data storytelling is the affinity for eye-catching aesthetics presented by visuals.

Numerous studies and research on human psychology and perception show that we process visual information far more quickly than written text or facts. As a result, organizations are keener on employing Visualization Tools to better understand scenarios as varied as Customer Sentiment, Real-Time Sales, Market Behavior, and more. By using Visualization Dashboards and representations like Heat Map Google Sheets, you can get deeper context on important Numbers, Trends, Metrics, and Key Performance Indicators (KPIs).

In this article, you will learn how to build visually effective Heat Map Google Sheets that will help you better understand your company’s performance and speed up your decision-making process.

Understanding Heat Maps for Data Visualization

One of the emerging Visualization Techniques that are being used widely today is Heat Map Visualization. With Heat Map Visualizations, you can visually see the distribution of data points on a Geographic Region or in a Tabular Matrix, where the individual values contained are represented as colours.

Since businesses typically deal with structured data, a Heat Map is a powerful tool for cross-examining multivariate data by placing variables in rows and columns where you can Color-Highlight Important Data containing cells within the table. This is achieved by using a Warm-to-Cool Color Spectrum to highlight Behavioural Data. Color-coding is used for Categorical Data, but Numerical Data requires a colour scale that blends from one colour to the next to show the difference between high and low values.

Heat Maps make it easy for you to visualize complex data and understand it at a glance when interpreting them for use in research and design. They allow you to see more information about an entity or a data point based on certain variables within their dataset. Heat Maps are useful for presenting variation across many variables, revealing patterns, indicating if variables are analogous to one another, and determining whether there are any relationships between them.

It is important to note that it can be challenging to correctly discern the distinctions between colour shades and extract particular data points from them unless the Raw Data is included. Hence, Heat Maps are better suited to portraying a more generalized picture of Numerical Data because of their reliance on colour to express values. Also, Heat Maps require a Legend for it to be read correctly. If one of the rows or columns is set to time intervals, Heat Maps may also be used to demonstrate how data evolves over time.

Introduction to Google Sheets

Google Sheets is a free web-based Spreadsheet software created by Google as part of their Google Drive Office Suite, which competes with Microsoft Office. The Google Office Suite (Workspace) consists of Gmail, Meet, Drive, Chat, Docs, Slide, Sheets, Forms, Keep as core office apps. It also contains apps like Jamboard, Cloud Search, Voice, Groups, Classroom, Vault, and many others.

Google Sheets is used for any activity involving the recording and analysis of data i.e. from Digital Marketing to Financial Modeling and from Record Management to Statistical Analysis. You can use Sheets to build Dashboards, write Formulas, and even Develop Applications too.

Google Sheets can support XLS, XLSX, XLSM, TXT, ODS, and CSV file format, making it simple to read and convert into Microsoft Office files directly from Google Drive. Since Google Sheets is an online Spreadsheet Software, you can also Share and Work on the same document with numerous people in Real-Time, recording modifications, changes, and recommendations.

In addition, being a Cloud-based Platform, Google Sheets integrates well with other online Google services and third-party sites. Other benefits of being a Cloud-based tool include access to information from anywhere, any time, and on any device. 

While the Google Sheets interface is similar to that of Microsoft Excel, the only difference is that Google has reduced the clutter and the number of displayed interface elements. Although Google Sheets can also be accessed offline, it does not offer flexibilities like MS Excel. 

Prerequisites

• Working Knowledge of Spreadsheets.
• A Google Account.

Steps to Create a New Spreadsheet on Google Sheets

The process is pretty simple for you to get started on Google Sheets. To create a new Spreadsheet in Google Sheets, follow the steps below:

• Step 1: On the Google Drive Dashboard, Click on New. 
• Step 2: Then click on Google Spreadsheet. A Spreadsheet will appear in a new browser tab, you can start working on this Blank Spreadsheet. Alternatively, you can hover the mouse cursor on ‘Google Spreadsheet,’ and on the right drop-down list, select either a Blank Spreadsheet or choose one from a Template.
• Step 3: To name your Spreadsheet, locate and select Untitled Spreadsheet at the top left of the page. Type a name for your Spreadsheet, then hit Enter.

Note: You can also click on the Google Suite Icon on the Homepage of Chrome Browser, scroll down and select the Sheets icon.

Steps to Build Heat Map Google Sheets

With Google Sheets’ new addition of conditional formatting (a few years ago), you can transform any data set into colourful Heat Map Google Sheets in just a few simple steps. Not only is this useful for spotting trends and patterns, but it also eliminates the need for a separate Chart or Graph.

We will discuss the following two steps to create your own Heat Map Google Sheets:

• Step 1: Getting Started with Heat Map Google Sheets
• Step 2: Highlighting Specific Values

Step 1: Getting Started with Heat Map Google Sheets

For creating Heat Map Google Sheets, follow the simple steps below:

• Select the data in the Google Spreadsheet.
• Select Format and then click on Conditional Formatting. This will open a Conditional Format Rules Panel.
• In the Color Scale panel, select Preview under Format Rules and choose a colour spectrum.
• Select the colours for your Minpoint, Midpoint, and Max point.
• Adjust your Midpoint to a Percentile.

Step 2: Highlighting Specific Values

Sometimes you may want to introduce a condition for the given data, for example, in a Datasheet containing information about employees and their respective salaries, you may want to highlight the cells containing a Salary amount of more than $3000 per annum. In that case, follow the steps shown below:

• Highlight all the data.
• Go to the Conditional Format Rule Window, Click on Add New Rule.
• Under Single Color Pane, Select the rule “Greater than” from the drop-down list.
• Enter the value 3000. You can also choose to display the output in Bold, Italic, or Underlined. 
• Click Done. The resultant Heat Map Google Sheets will show the cells having a Salary value of $3000 and above for the corresponding employees.

Limitations of Building Heat Maps in Google Sheets

Heat Map Google Sheets gives you an opportunity to display your Data in a visually appealing way as well as provides better Business Insights. Though, while using Heat Map Google Sheets you may encounter the following challenges:

• Because Heat Maps rely significantly on colour, it’s critical that they’re made in an accessible manner. Whenever possible, the colour scheme chosen in the Heat Map should fulfil Color Contrast and Density Criteria so that all users or receivers of the Heat Map may benefit from the colour indicator. 
• Special attention must be paid if the viewers are colourblind. In case, inaccessible colours are used, you may risk losing the layer of colour as a means of conveying your point, and the image becomes difficult to comprehend.
• Also, it is hard to deduce the numerical value corresponding to a particular hue with adequate precision when employing a table look-up approach to answer specific inquiries. 
• Further, the resulting information in Heat Map Google Sheets is frequently not grouped in such a way that patterns may be discerned. Therefore, it is sometimes difficult or impossible to discern anything about general overarching patterns without clustering.

Conclusion

Since Heat Map Google Sheets are both easy to comprehend and attractive to look at, they can appeal to a wider range of consumers, including both creative and logical thinkers. In addition, the adaptability of Heat Map Google Sheets allows them to be employed in a number of circumstances rather than being confined to a single time instance.

Though, as organizations grow, the number of data sources increases; generating tremendous volumes of Data. Regularly Handling, Compiling, and Integrating all of that data manually is a time-consuming task and requires resources that could rather be utilized on important Business activities. As discussed earlier, visualizing all this data just with Heat Map Google Sheets might not be the best way to move ahead. An elegant solution to the above problems can be provided by a Cloud-Based ETL Tool like Hevo Data.

Visit our Website to Explore Hevo

Hevo Data, a No-code Data Pipeline, helps you integrate data from different data sources like Google Sheets, Microsoft Excel into a Data Warehouse or a destination of your choice to be effectively visualized in a Business Intelligence Tool. It is fully automated and secure which doesn’t require you to write any code!

Hevo, with its strong integration with 100+ sources & BI tools (Including 40+ Free sources like Google Sheets), allows you to not only export & load data but also transform & enrich your data & make it analysis-ready so that you can focus on your key business needs and perform insightful analysis using BI tools.

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