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This article explains how to use Excel 3D Maps end to end for professional geospatial analysis, from preparing location data and configuring map layers to designing time-based tours, custom regions, and performance-optimized dashboards.
1. Understanding Excel 3D Maps as a Geospatial Analytics Engine
Excel 3D Maps is a three-dimensional data visualization tool that plots geographic and time-based data on an interactive globe or flat map, using Bing Maps as the base layer. It supports high row counts, typically more than a million rows when driven from the Excel Data Model, and is available in modern desktop versions such as Microsoft 365, Excel 2024, 2021, 2019, and 2016 for Windows.
3D Maps is the evolution of the earlier “Power Map” add-in, which appeared as a separate add-in in Excel 2013. The core capabilities are mapping, discovering insights, and telling data stories with cinematic tours.
Typical use cases for Excel 3D Maps in geospatial analysis include the following scenarios.
- Sales and revenue by country, region, state, or city over time.
- Store, branch, or site-level KPIs plotted at precise coordinates.
- Logistics flows, shipping volumes, or delivery performance by route or hub.
- Environmental or sensor data (for example, air quality, temperature, or traffic counts) at specific locations.
- Public statistics such as crime incidents, health indicators, or demographic trends.
3D Maps is especially valuable when the analytical question is explicitly spatial or spatio-temporal, such as identifying clusters, regional outliers, or the spread of an event along a timeline. Traditional 2D charts and tables can show numeric relationships but do not reveal geographic patterns as effectively as a geospatial view.
2. Preparing Geospatial Data for 3D Maps
Successful geospatial analysis in Excel 3D Maps depends primarily on how location and time fields are prepared. Poorly structured data leads to geocoding errors, misaligned points, and unreliable insights.
2.1 Supported Geographic Fields
3D Maps recognizes several types of geographic information when mapping your data.
- Country or region name.
- State, province, or region.
- County, district, or administrative subdivision.
- City, town, or suburb.
- Postal code or ZIP code.
- Street address (for finer resolution, although bulk address geocoding can be slow).
- Latitude and longitude coordinates.
For robust geocoding, it is best to provide a combination of fields (for example City + State + Country) rather than relying on a single ambiguous name like “Springfield”. This gives Bing Maps more context to resolve the location correctly.
2.2 Structuring Data in Tables or the Data Model
3D Maps expects the data source to be an Excel table or, preferably, a Data Model (Power Pivot). Each row must represent a single record, such as a transaction, site, or aggregated measure for a specific period. Column headers should be descriptive text, not data values, because the headers become field names in the 3D Maps field list.
A typical minimum set of fields for geospatial analysis in 3D Maps is as follows.
| Field role | Column example | Data type | Notes |
|---|---|---|---|
| Location | Country, State, City, PostalCode, Latitude, Longitude | Text or decimal | At least one location field is required; combining multiple fields improves accuracy. |
| Value | SalesAmount, Volume, Incidents | Numeric | Defines bar height, bubble size, or color intensity. |
| Category | ProductCategory, Channel, SiteType | Text | Splits each location into multiple colored segments or series. |
| Time | Date, Month, Quarter, Year, Timestamp | Date/time | Allows animation of changes over time in 3D Maps tours. |
2.3 Cleaning and Normalizing Location Data
Before opening 3D Maps, inconsistencies in location fields should be resolved.
- Standardize country names (for example, “United States”, not a mix of “USA”, “U.S.”, “United States of America”).
- Use consistent abbreviations for states or regions and avoid mixing codes with full names in the same column.
- Validate postal codes and ensure that they match the intended country.
- For latitude and longitude, ensure they are numeric and correctly signed (negative for western longitudes and southern latitudes).
Power Query in Excel is effective for trimming spaces, unifying case, splitting combined location strings, and mapping inconsistent names to standardized labels before exposing the data to 3D Maps.
2.4 Example of a Clean Geospatial Table
The following is a compact example of a location table suited for 3D Maps.
Country State City Latitude Longitude SalesAmount Date ---------- ---------- ----------- -------- --------- ----------- ---------- United States CA San Jose 37.3382 -121.8863 152000 2024-01-31 United States WA Seattle 47.6062 -122.3321 98000 2024-01-31 Germany BY Munich 48.1351 11.5820 76500 2024-01-31 Japan 13 Tokyo 35.6762 139.6503 220000 2024-01-31 This design provides both high-quality geography (country, state, city, coordinates) and a clear measure (SalesAmount) and time field (Date).
3. Creating an Excel 3D Map for Geospatial Analysis
3.1 Enabling and Launching 3D Maps
After preparing the data, the core steps to start a 3D Map tour are as follows.
- Select any cell within the table or a PivotTable that uses the Data Model.
- On the Insert tab, choose 3D Map in the Tours group.
- If this is the first use in the workbook, select Open 3D Maps or New Tour.
- Excel opens a separate 3D Maps window with an interactive globe and the Layer Pane.
3D Maps automatically attempts to geocode the location fields using Bing Maps. The mapping status is indicated in the Layer Pane, where each field is assigned a geographic role such as City or Postal Code. Misclassified fields can be corrected using the drop-down list next to each field name.
Note : If many records are not recognized, reduce ambiguity by providing more granular location fields (for example, City plus Country) or switching to latitude and longitude coordinates.
3.2 Configuring Layers: Location, Value, Category, and Time
Each layer in 3D Maps describes how a particular dataset is rendered on the map. Key configuration areas include Location, Value, Category, and Time.
- Location: Assign one or more geographic fields. Examples include Country, State, City, PostalCode, or Latitude/Longitude pairs.
- Value: Assign numeric fields that define the height of columns, size of bubbles, or intensity of heatmaps.
- Category: Optional; splits each geographic point into colored segments or groups (for example, channel, product family, or customer type).
- Time: Enables the time slider and animations. This typically uses a Date or DateTime field.
Designing layers deliberately is crucial. For example, a sales layer might use City as the location, SalesAmount as Value, and ProductCategory as Category while using InvoiceDate as Time. A separate layer in the same tour might show units sold or margin, potentially against a different geographic level such as State or Country.
3.3 Choosing the Right Visualization Type
3D Maps supports several visualization types, each suited to particular geospatial questions.
- Column: Ideal for comparing magnitudes across locations, such as revenue or volume by city. Columns are easy to interpret when density is moderate.
- Bubble: Useful when the relative area of a circle is more intuitive than column height, especially for rate-based metrics or when overlapping markers are acceptable.
- Heatmap: Highlights density or intensity of values across space, making it suitable for demand hotspots, incident concentrations, or coverage analysis.
- Region: Fills entire regions (for example, countries or states) with colors based on aggregated values, similar to a choropleth map.
For analytical workflows, it is often effective to start with a Region or Heatmap view to identify patterns at a high level and then switch to Column or Bubble to inspect specific locations.
3.4 Example: Building a Regional Sales 3D Map
A typical workflow for a regional sales geospatial map includes the following steps.
- Prepare a table with Country, State, City, SalesAmount, and InvoiceDate fields.
- Insert a 3D Map and create a new tour.
- Set Location to City and Country, Value to SalesAmount, and Time to InvoiceDate.
- Select Column or Region as the visualization type.
- Adjust aggregation (sum, count, average) in the Layer Pane depending on the metric (for example, sum of SalesAmount or count of Orders).
- Refine color scales and themes to emphasize high and low performers.
At this point, the map already functions as a dynamic geospatial dashboard. The analyst can rotate the globe, zoom into markets, filter categories, and play the time slider to see how performance evolves.
4. Advanced Geospatial Techniques in Excel 3D Maps
4.1 Using Latitude and Longitude for Precise Locations
For high-precision mapping, such as store locations, sensor nodes, or site inspection points, latitude and longitude fields provide more control than name-based geocoding. Excel 3D Maps allows direct mapping of numeric Latitude and Longitude columns.
Typical steps for a coordinate-based scenario are as follows.
- Store coordinates in decimal degrees (for example, 37.7749, -122.4194).
- Format the dataset as an Excel table.
- Launch 3D Maps and assign Latitude and Longitude fields under Location.
- Optionally keep City, State, or SiteName fields in the dataset for labeling, tooltips, or legends.
Coordinate mapping is crucial for engineering, environmental, and logistics applications where multiple locations may share the same city name but differ in exact position.
4.2 Calculated Fields for Derived Metrics
Excel formulas or Power Pivot measures can derive more meaningful geospatial metrics before visualization. Examples include sales per capita, incident rate per thousand inhabitants, or capacity utilization per site.
For a simple derived column in a table, an Excel formula could be:
=[@SalesAmount] / [@Population]This produces a rate-based metric that can be visualized as a bubble size or heatmap intensity, making comparisons between regions with different population sizes more meaningful.
4.3 Time-Based Storytelling with Tours
One of the strongest features of 3D Maps is the ability to create tours. A tour consists of scenes, each representing a camera position, layer combination, and filter state.
- Create multiple scenes to show progression: global overview, regional drill-down, city-level hotspots, and a closing summary.
- Configure transitions between scenes (for example, fly over, fade) to guide viewers through the narrative.
- Use the time slider in each scene to animate changes by day, month, or year.
- Export the tour as an MP4 video for use in PowerPoint or online presentations.
For management reporting, a well-designed tour can replace multiple static charts and maps by combining spatial and temporal patterns into a single, cohesive story.
4.4 Combining Multiple Layers for Multi-Metric Analysis
3D Maps allows multiple layers in the same scene, enabling analysts to overlay different metrics or datasets.
- Layer 1: Revenue by State (Region visualization).
- Layer 2: Number of active sites (Column visualization) at major cities.
- Layer 3: Incident count or downtime (Bubble or Heatmap visualization).
Properly configured, this multi-layer design reveals how revenue, network footprint, and risk indicators interact geographically. Transparency and color choices should be adjusted to avoid visual clutter.
5. Custom Regions and External Geospatial Data
Some scenarios require mapping to custom regions that do not align with standard political boundaries, such as sales territories, health zones, or utility service areas. Excel 3D Maps can work with custom region files in formats such as shapefile or KML, provided they use a compatible coordinate system (commonly WGS 1984).
Typical steps for custom regions are as follows.
- Prepare or obtain a shapefile or KML with the required custom boundaries in a supported projection (typically WGS 1984).
- Assign unique region IDs in both the spatial file and the Excel data table (for example, TerritoryID or ZoneCode).
- Import the custom region data in 3D Maps and map the Excel data to the region ID field.
- Use the Region visualization type to color each custom area based on metrics such as coverage, volume, or risk score.
This approach allows domain-specific geography to drive the visualization, which is often more meaningful than default country or state boundaries.
6. Integrating 3D Maps into Excel Analytics Workflows
6.1 Power Query and Data Model Integration
Power Query (Get & Transform) is typically the best entry point for assembling geospatial data. It can extract, transform, and load data from multiple sources, including CSV files, databases, and web APIs. Once data is cleaned and merged, it is loaded into the Excel Data Model, which 3D Maps can then use as a rich backend.
Benefits of using the Data Model for 3D Maps include the following advantages.
- Handling large row counts beyond normal worksheet limits.
- Defining relationships between tables (for example, FactSales and DimLocation) instead of duplicating location information.
- Creating DAX measures for advanced calculations that can be reused in PivotTables and 3D Maps.
6.2 Linking 3D Maps with Dashboards and Reports
3D Maps does not replace standard Excel dashboards; instead, it complements them as a specialized geospatial component.
- Use PivotTables and charts for KPIs, trends, and tabular summaries.
- Embed screenshots of 3D Maps views into summary dashboards to anchor narratives spatially.
- Export tours to video and link them from PowerPoint or from shared folders for stakeholders.
For governance, the underlying data pipeline (Power Query queries, Data Model, and measures) should be documented separately so that 3D Maps remains a visual interface on top of a well-managed data foundation.
6.3 Data Refresh and Maintenance
When data is refreshed via Power Query or manual updates, 3D Maps can reuse the existing tour definition. As long as field names and data structure remain stable, refreshing the source and reopening 3D Maps will reflect the latest values without rebuilding scenes.
Note : Structural changes such as renaming columns, removing fields used as Location or Time, or replacing the Data Model may break existing tours and require reconfiguration.
7. Performance and Design Best Practices
Although 3D Maps can visualize large datasets, thoughtful design improves performance and interpretability.
- Limit unnecessary fields. Remove unused columns from the table or Data Model to reduce memory footprint and simplify the field list.
- Aggregate where possible. Instead of plotting every transaction, aggregate by day and city or by month and state, depending on the analytical need.
- Avoid overplotting. In dense urban areas, too many points can overlap. Switch to Heatmap or Region visualization for such data, or aggregate at higher geographic levels.
- Use meaningful color scales. Select colors that clearly distinguish high, medium, and low values and remain legible for color-blind users when possible.
- Label sparingly. Excessive labels and data cards obstruct the map. Use them for key locations only, or rely on tooltips that appear on hover.
- Use consistent basemaps. For multi-scene tours, keep the same basemap style and general zoom level unless a deliberate change in perspective supports the narrative.
From a communication perspective, each tour should answer a small number of well-defined questions (for example, where revenue is concentrated, how a phenomenon spreads, or which sites underperform) rather than trying to display all possible metrics at once.
FAQ
Which Excel versions support 3D Maps for geospatial analysis?
3D Maps is available in Excel for Microsoft 365 and recent perpetual desktop versions such as Excel 2024, 2021, 2019, and 2016 for Windows. Earlier versions, such as Excel 2013, provided similar functionality through the separate Power Map add-in. Availability may vary by edition, and web or Mac versions may have limited or no support.
Does Excel 3D Maps require an internet connection?
Yes. Because 3D Maps uses Bing Maps as its mapping service, an active internet connection is required for geocoding and for loading the basemap tiles. Once the basemap is cached, panning and zooming may continue to work for a time, but geocoding new data or switching regions still depends on online connectivity.
What is the difference between 3D Maps and standard map charts in Excel?
Standard map charts in Excel are two-dimensional, directly embedded in worksheets, and optimized for static choropleth-style visualizations. They are good for simple region-level comparisons. 3D Maps provides an interactive globe or flat map, supports multiple visualization types, handles larger datasets via the Data Model, and includes time-based animation and cinematic tours. It is better suited for exploratory geospatial analysis and storytelling.
How should ambiguous locations be handled in 3D Maps?
Ambiguous place names should be clarified by providing additional context, such as including State or Country fields together with City. For highly precise requirements or for repeated geocoding issues, it is usually better to supply latitude and longitude coordinates. Data preparation steps in Power Query can standardize ambiguous names and ensure that each row maps to the intended location.
Can Excel 3D Maps work with live or frequently refreshed data?
Yes. When the geospatial dataset is loaded via Power Query or other external data connections into the Data Model, scheduled refreshes or manual updates can feed new values into existing 3D Maps tours. As long as the schema remains stable, the configured layers, scenes, and tours adjust to the refreshed data automatically, which makes 3D Maps suitable for recurring reports and periodic updates.