D&B Market Insight Release Notes. July 2016

Transcription

1 D&B Market Insight Release Notes July 2016

2 Table of Contents User Experience and Performance 3 Mapping.. 4 Visualizations.... 5

3 User Experience and Performance Speed Improvements Improvements have been made to the central job polling and storage to reduce latency and improve manageability. This should lead to faster query response for users. Compressed Static text virtual variables The storage of textual virtual variable processing has been completely rewritten to always use compression. This means the creation of textual virtual variables is less problematic. Record comments in the Expressions boxes The Expressions tool now allows comments to be saved in the text of the expression. Comments are shown in grey and can be identified as any text that falls between a pair of /* */ symbols.

4 Mapping New Wizards To ensure that users are able to maximize the use of the Geo module now that MapPoint is no longer supplied by Microsoft, we have extended the mapping functionality with Bing Mapping to match that provided previously with MapPoint. Bing Mapping within the Geo Module now offers the following wizard driven functionality: Drive Zone create virtual variables showing drive-time zones around one or a list of center points. Geocoding create latitude and longitude variables from address data. Point to Point calculate the drive time or distance between records and a nominated point. NOTE Please note that these wizards do a lot of processing in the background so should be used sensibly and can take some time to process. Improved Color scheme for PinPoints Bug Fixes for Multi-Layer Maps Work has been done to rectify issues where pins were lost on multi-layer maps.

5 Visualizations Switch between visualizations with an underlying cube The Cube tool breaks data down into a tabular structure so that users may analyze numeric measures on their selected records. This type of Cube analysis powers many of the visualizations within Market Insight and improved functionality now allows users to move between these visualisations. This functionality may be useful in order to view the following: Word-Cloud to Cube (to see the numbers behind the picture) Cube to Tree (to identify the highest value cells) Venn to Cube (to move beyond 5 segments) Map to Cube (to see the numbers behind the map) Charting to Cube (to see the numbers behind the chart). To summarize, this means that the user can now seamlessly convert a visualization based on a Cube (i.e. Cube, Tree, Map, Venn, Word Cloud) to a Cube, Tree, Venn, or Word Cloud. In addition, you can now also convert from Charting to a Cube. Note: The conversion will be validated based on the underlying cube content and only applicable conversions will be offered. For example, only a cube analysis containing up to five query sets can be converted into a Venn Diagram. This functionality is initially available from a right-drag of the page handle onto the workspace. This may evolve over time depending on feedback from usability testing. In the example below, the Word Cloud has been right dragged onto the workspace (to show the context menu) and this has been converted to the equivalent Cube shown on the right hand side. This enables you to see the data broken down into a tabular, numeric structure in order to further analyze and drag and drop off the cells that are of interest.

6 Rename and reorder statistics and rename dimensions within Cubes This development improves the statistic and dimension handling in the Cube tool. Statistics can now be renamed and reordered. A simple click and drag on the pop-up Statistics list will reorder. You can rename a Statistic by editing it and choosing Use Custom Statistics name. Dimensions can be renamed and for queries, querysets and numeric bandings. The dimension headers can be renamed using the Edit Dimension Value. This new functionality gives you more control over Cubes and makes them easier for others to understand. The example below shows a dimension header being renamed.

7 Improvements to the Scatter Chart within the Data Grid Usability studies have enabled us to further refine the view of the Scatter Chart within the Data Grid. When a categorical variable is used, the points are now all colored according to that categorical variable making it easier to identify points. Furthermore, clicking on one of the categories (as seen below) highlights just those points (but with improved opacity to make the points visible). In addition. you can now zoom into the whole chart on both horizontal and vertical axes using the scroll/ zoom bars. The scatter plot can be animated in the order of records in the data grid, for example, showing the spread of the points over time.