Create the Analytics desktop for your Google sheets

Photo via editor Chatgpt

# Entry

Google Sheets navigation desktop is a powerful way to visualize the progress of the project, compare tasks and quickly identify everything that requires your attention. You can easily determine the priorities of your work, follow the bottlenecks and take real -time actions. What’s more, when you combine Google Sheets dashboard with resources such as Google Analytics, Salesforce or Github, your navigation desktops can effectively refresh when the data is modified or changed.

In this article I will go to how to build a basic navigation desktop using Google sheets.

# Why consider the navigation desktop for your Google sheets?

Google Sheets navigation desktop is a very useful tool that will assist you visualize and track data on several different platforms. Simply clicking Botton, you can combine data from various spreadsheets to display data on charts, tables and charts so that we can analyze our business or project.

You can even create alerts that automatically sent so that you can keep an eye on changes introduced to navigation desktops and observe whether trends are developing that may require repair.

Creating a functional and visually attractive navigation desktop in Google sheets consists of a few uncomplicated steps. Let’s look at them now.

# 1. Importing and organizing data

Start by organizing data in a clear, tabular format. To start, we will exploit a set of data on the flower sales dummy. You can copy it to get it this sheet template With the database already attached (and solution!).

If you want to exploit any other data source, you can easily send a CSV file or connect a Google sheet with a specific source of data using its connectors. When the data is in our environment, remember:

• Make sure the data is neat and consistent (e.g. without empty cells or mixed formats)
• Utilize checking the correctness of data to create a developed menu for categories or statuses
• Attach the time stamp column if you plan to follow trends in time

# 2. Generate the chart

After preparing the data, display the part you want to analyze and go to insertion and then the chart. Google sheets will introduce the chart to the sheet, initially as an empty canvas.

You will work with two main cards to configure your chart:

• Configuration: where you choose the chart type (e.g. line, belt, cake) and define the data range. Remember to attach all necessary columns representing axles or variables.
• Adjust: where you adapt the appearance, labels, colors and layout to adapt to your needs or reports. Utilize this section to adjust the chart to obtain transparency, readability and impact.

Remember about: The number of columns contained in the data range will determine how many dimensions (e.g. x and y axes) can display the chart.

Screenshot of Google sheets

// 2.1 Carc Carda or Mages

Rescuer cards are ideal for distinguishing key performance indicators (KPIs) or one value indicators, such as total income or average discount.

To create one, you can first insert a modern chart and choose the type of results chart.

Then go to the configuration card, define the data range, the Ordotal column to display complete sales.

After this, the basic results card will appear immediately. Then you can adjust it on the Adjust:

• Customize the scale. In this example we will choose millions.
• Add a prefix or suffix.
• Set the title, such as “sales revenues”, and level both the title and the metric value to the center.

Here’s what the last results card can look like:

You can repeat this process to display other KPIs:

1. Units sold, adding a quantitative column
2. Average discount, calculating the average discount column

These results cards give a quick summary of your most essential indicators.

// 2.2 linear charts

Linear charts are ideal for tracking trends and time changes. To create one:

• Insert a modern chart and select the line chart type
• On the configuration card, select two data ranges, one for the X axis (e.g. time or date column) and one for the Y axis (such as total orders or sales revenues)

This configuration allows you to visualize how the indicator is evolving. Add a descriptive title, such as the transient evolution of revenues to make the chart effortless to interpret. After configuring, the table should clearly show the trend of revenues in the selected period. Here is my last result:

// 2.3 Charts of bars and columns

Post -columns and columns are the best option to compare values in different categories. In this example, we want to determine which product categories offer the highest average discounts:

• Insert a modern chart and choose the type of belt chart.
• Select two data ranges on the configuration card. One for the category axis (product category). Another values for the axis (discount column, using average aggregation)
• Adjust the chart by assigning separate colors to each belt to enhance visual transparency.

// 2.4 Bar charts and columns

The wheeled charts are useful to display the proportion and understand how different parts contribute to the whole. In this case, we visualize the distribution of revenues by product category:

1. Insert a modern chart and choose the type of circular chart.
2. Select the appropriate data ranges on the configuration card. One for the category (e.g. product category) Another for values (like total revenue per category)
3. Adjust the chart by assigning separate colors to each patch to get better readability.

This will generate a clear, proportional division of revenues between categories, helping to quickly see which segments enhance the highest income.

Now we have all our charts! Immediately we will receive the final version of our navigation desktop. Another natural step is to allow users to choose data to see what leads to it.

# 3. Adding a slit for data filtering

To offer flexibility and lively access to the navigation desktop as the amount of data increases, you can exploit the exchange. Slipping are interactive filters that allow users to create their own specific filters based on some columns.

First go to the data and select Add to the edge.

Then select the whole set of data as a Plcer range and select the column you want to filter (like a region, product category or date).

The semi -education automatically filters all navigation desktops, charts and visualizations that are connected to it, based on the values selected by the user.

In our example, we will add two activical slicers that allow us to create filtered navigation desktops, one for the Orderpe and the other for the productcatemars category to make it easier to examine a set of data.

# 4. Generate the dashboard with many charts

Now, when you made your charts and created activation, we will put everything on one last navigation desktop. To do this, we will have to:

• Create another sheet for the navigation desktop
• Place a clear title on the top of the modern sheet to sum up the content of the navigation desktop
• Organize and group your visualizations in similar or related sections
• Align your charts and cut together to maintain a fairly neat and professional navigation desktop

Thanks to only a few patches of the system, you will transform the chart collection into an interactive, effortless -to -read navigation desktop ready to make decisions and presentations.

# Application

Google Sheets offers a versatile and available way to build navigation desktops that assist to follow performance, explore trends and make decisions based on data, all without leaving the browser.

By following this guide, you have learned to effectively construct and import data; Create different types of charts for different insights; Add interactivity by cutting; And design a polished, professional navigation desktop system.

Regardless of whether you manage projects, follow sales or monitor KPIs, Google Sheets dashboard can become your real -time observation tool, does not require coding.

Josep Ferrer He is an analytical engineer from Barcelona. He graduated from physics engineering and is currently working in the field of data learning used for human mobility. He is the creator of part -time content focused on learning data and technology. Josep writes about all AI things, including the exploit of a ongoing explosion in the field.