Introducing Heat Map Explorer 2.0 Heat Map Explorer 2.0 introduces many new features to help you visualize and analyze your data. These features include: New Map Types New Map Styles New Visual Benchmarking Improved Data Aggregations New Analysis Controls Improved Filtering & Selection Download Evaluation Try it free for 14 days. Buy Now Purchase your copy online today. Guaranteed satisfaction.

New Map Types Different types and styles of visualization are appropriate for answering different questions and Heat Map Explorer can now answer an even broader range of questions. Several new map types have been added to the original Squarifed, Strip and Bar maps. Chain Maps Horizontal and vertical chain maps stack data items within rows or columns to make it easy to see the number of items in each category. These maps are especially useful for pipeline, time and progress analysis. Histogram Maps Histogram maps divide the selected numerical column into 100 equal bins and stack individual data items into bins that correspond to their value for that column. These maps show how items are distributed across the range of values and are very useful for identifying outliers or seeing shifts in results or behavior across different categories. Column Maps The column and column bar maps use the settings for Group By for rows and Then By for columns in order to build a uniform grid, with individual records then arranged in a squarified or bar map within each grid cell. These maps make it easy to identify gaps within categories since equivalent Then By categories are lined up vertically. Column maps are particularly useful for looking at how data in different categories changes over time by setting Then By to a time-period column. Group Bar Maps The group bar map builds a bar chart with bars determined by the Group By category, but arranges items within each bar as a regular squarified map. This map makes it straightforward to compare the relative contributions of different categories while still offering visibility into the full portfolio of results.

New Map Styles Heat Map Explorer 2.0 introduces several new styles that can be applied to maps to make them more readable for specific types of analysis. Cluster The Cluster style colors group borders based on the aggregate color value of each group. Group colors make it easy to see group-level performance issues that may not be obvious just by viewing the collection of cells. Combined with customizable aggregations, the Cluster style can be a powerful way to analyze data. In the picture below, color is keyed to a performance measure with an average aggregation, allowing us to easily see the average performance for each group as a whole. Classic The Classic style is a compact style which eliminates the clutter that can happen with the Window and Cluster styles when there are lots of groups, and minimizes size distortion among leaf level cells. This makes it ideal for large data sets with lots of top-level groups. Zen When maximum display space is needed for your data, Zen style provides a basic and compact view of your data. It eliminates all borders and only displays labels for leaf-level cells. It is ideal for very large data sets where the goal is to get a broad overview of the data. Window The Window style emphasizes the hierarchy of your data, making it easy to see the distribution of groups at each level and to identify which group an individual cell belongs to. The large group border also makes seeing a group's information easy; just hover over the border and the information will appear in the info panel. The Window style was the only style available in Heat Map Explorer 1.0.

New Visual Benchmarking A common way to understand performance is to benchmark individual performance against a standard or against an average. Such calculations are at best tedious and at worst nearly impossible in Excel. Heat Map Explorer 2.0 makes this easy with our new visual benchmarking functions. Cell Benchmark Cell benchmarking allows you to select a cell as a standard, then visually see how all the other cells in a heat map compare to that standard. When a cell benchmark is created, it calculates the percentage difference between the value of the color field for each cell in the heat map and the benchmark cell. Cells are colorized based on this percentage difference. For instance, the left picture below shows the original data where color has been mapped to the % change of each stock for the NASDAQ 100. The right picture shows the same stocks benchmarked against Intel. Stocks with a larger % change than Intel are colored green, while those with less of a % change than Intel are colored red. Before Cell Benchmark Color Shows % Change After Cell Benchmark Color Shows Difference From Intel Group Benchmark Group benchmarking allows you to visually see how cells compare to others within their group. When a group benchmark is created, it calculates the average color value of each group, then calculates the percentage difference between this average and the color value of each cell within the group. Cells are colorized based on this percentage difference. For instance, the left picture below shows the original data where color has been mapped to the % change of each stock for the NASDAQ 100. The right picture shows the same stocks benchmarked against the average of each stock's sector. Stocks with a larger % change than their sector are colored green, while those with less of a % change than their sector are colored red. As you can see, most stocks in most groups are not far from the average, but there are a few outliers that may be easily seen in the topmost left and right groups. Before Group Benchmark Color Shows % Change After Group Benchmark Color Shows Difference From Group Average

Improved Data Aggregations In Heat Map Explorer 1.1, when individual data items were grouped, summed values were automatically computed for the group for all numeric fields. These values could be viewed in the details pane when the mouse hovered over a group. The aggregate values were unaffected by the filters that were applied so it was difficult to perform what-if analysis and view the resulting aggregations. In version 2.0, aggregate values now reflect the filters that have been set. This means you can apply several filters and see how those filters affect the aggregate values for each group. To see the aggregate values for the entire data set, you can now hover over the "Home" button on the navigation trail. Additionally, you can now customize the aggregation formula used to calculate the aggregate value for groups. Heat Map Explorer 2.0 now supports the following aggregation formulas: Sum Average Median Minimum Maximum Standard Deviation (Sample & Population) Count Weighted Sum Weighted Average Features like the Cluster style and take advantage of these new aggregation functions to give you deeper analysis of your data.

New Analysis Controls Heat Map Explorer expands the range of visual analysis you can perform with the new Detail Level slider, and allows you to better share your insights with the new Notes tab. Detail Level Control When the map is composed of a very large number of individual records, it can be convenient to hide individual details until you have zoomed in and are ready to consider them. The Detail Level slider, when activated, shows only groups, colorized by the aggregated value of all line items within each group, as shown below. Showing All Detail Hiding Leaf Detail Notes Tab When analysis brings insight that you need to share, or when you need to record thoughts or follow-up items and keep them together with the map that gave rise to them, the new Notes tab gives you a place to record them. These notes are included with you print a heat map or generate a PDF.

Improved Filtering & Selection Filtering and selection are critical for identifying actionable data and exporting those selections to e-mail, Excel or Word. Improvements to these features now make this easier. Improved Filtering Filtering in Heat Map Explorer 2.0 has been improved in two ways. First, filters are now reflected in aggregate values computed for all numerical fields. For example, a group containing four values of 10, 20, 20, 50 would have an unfiltered sum aggregation of 100. If a filter excludes values under 15, only the last three items will appear in the map, and the sum will show as 90. Heat Map Explorer 1.1 did not account for filtering and would have showed 100. In addition, sliders for numeric value filters now support both inclusive and exclusive ranges. Thus, the slider on the left includes values between $192K and $537.5K, while the slider on the right excludes the same range. Improved Selection Heat Map Explorer 2.0 makes selecting cells for export, printing or emailing significantly easier. New selection features include: Select Visible: Use filters and drill-down to limit the visible cells and then add or remove all the visible cells to your selection. Select Group: Select or unselect all the cells within a group. Select All: Select or unselect all the cells within the heat map. Invert Selection: Switch all selected cells to being unselected and vice versus.

Pricing & Options Heat Map Explorer Desktop comes in three versions suited to different types of users. Contact sales for more information on our server editions. Standard $1,295/user Create interactive heat maps of data in Excel spreadsheets and Access databases.   Professional $1,795/user Connect to Microsoft SQL Server, Oracle, Sybase and DB2 databases in addition to Excel and Access.   Viewer $495/user View, print and share interactive heat maps created by Standard or Professional Edition. All prices include 1-year product updates & e-mail support.     Download Evaluation Try it free for 14 days. Buy Now Purchase your copy online today. 30-Day Guarantee You'll be satisfied, or we'll refund your purchase. Contact Sales Call (800) 921-3623 or +1 (646) 964-6463 and press 1 to speak to a salesperson.