Wiki source code of Analyse des dépendances

Last modified by Aurelie Bertrand on 2026/07/06 16:22

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6 Dependency analysis is a mechanism that enables you to identify the relationships between the various elements of your environment.
7 For example, you can easily determine which dashboard pages use a chart, or identify all the charts that use a particular format.
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9 = Dependency analysis =
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12 When the tool is opened, the analysis runs automatically.
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15 The dependency analysis scans all DigDash elements, starting with roles. The more elements there are (Flows, data models, dimensions, measures, etc.), the longer the analysis may take.
16 If you are using a WLNK file server, all files on the server are analysed. If the server contains a very large number of elements, the analysis time may increase considerably.
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19 Once the analysis is complete, your entire environment is mapped out and you will be able to analyse categories of elements or specific elements.
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22 [[image:Dpeendency_analysis_en.png]]
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24 For example, to find out whether a format is being used, and by whom, apply the following filter:
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26 * In the **Filters** section, open the **‘Focus on** ’ drop-down menu to select **‘Format’:
27 **[[image:1783344601066-128.png]]
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29 * Then, in the **Display** section, change the display order from **‘contains** ’ to **‘used by'**:
30 [[image:1783344692585-931.png]]
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32 This way, the view displays all formats, and by expanding the ‘Formats’ items, you can see where they are used:
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34 [[image:Dpeendency_analysis_format_en.png]]
35 In the screenshot above, the **Euro **format **is **used by 11 charts in the **Retail** role.
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37 This allows you to identify precisely how all the elements in your environment are used.
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39 The **‘Backup’** button takes you to the page for **backing up your **data. See the page [[Backup and Restore>>doc:Digdash.deployment.configuration.backup_restore.WebHome]] page for further details.
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41 == Relationships between resources ==
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43 Please note that some links between resources are not immediately obvious.
44 It is important to bear in mind both directions: ‘**contains**’ and ‘**is contained in**’.
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46 === {{glossaryReference glossaryId="Glossary" entryId="Flux"}}Flow{{/glossaryReference}} (chart) ===
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48 A flow can be used in at least two different ways:
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50 * because it **is used within** a dashboard page
51 * because it **contains** a device, such as an email
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53 So, by using the “used” filter in “is contained in” mode, you can see charts that are not on any dashboard page, nor in any {{glossaryReference glossaryId="Glossary" entryId="fabrique de documents"}}document builder{{/glossaryReference}}. And yet they are identified as “used” because they contain a link to a device (document server, email, FTP, etc.).
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55 === Measure and dimension ===
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57 Measures and dimensions can be used in a wide variety of contexts (non-exhaustive list):
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59 * chart
60 * interaction
61 * hierarchy
62 * formatting
63 * objective
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65 However, a measure may also be used in none of these elements, and serve only to calculate another measure.
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67 = Other uses of dependency analysis =
68
69 == Studio: confirmation of actions ==
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71 In your day-to-day use of Studio, you will need to delete elements that may be used simultaneously in very different contexts, and potentially as a result of actions taken by other users.
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73 Thanks to dependency analysis, you will be notified of the use of the elements you wish to delete:
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75 [[image:Format_deletion_warning_en.png]]
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77 In the example above, 3 formats are to be deleted, but the confirmation window indicates that two of them are currently in use: **Euro**, **Nbr. abbrev..**
78
79 == Studio: on-demand analysis ==
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81 Still within Studio, you are not obliged to use the **Dependency Analysis** manager as your starting point.
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83 For example, by right-clicking on a chart, you can see at a glance where they are used:
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85 [[image:Dpeendency_analysis_flow_en.png]]
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87 The manager opens. The view is already filtered to show the selected chart and is in ‘is contained in’ mode.
88 You can then see at a glance that the chart appears on **a dashboard page**:
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90 [[image:1783346679740-536.png]]
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92 The same principle applies to data models, formats, document servers and all elements of your environment.
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94 == Saving ==
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96 The dependency analysis mechanism is also used transparently during **saving:**
97 you can select just one chart and all the elements on which it depends will be included in the restore archive (formats, colours, scripts, etc.).
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99 In the screenshot below, a single chart has been selected (by clicking on the numbers to the right of the tick box in the Wallet column):
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101 [[image:Roles_en.png||height="86" width="745"]]
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103 In the options available via the **Options** button at the top right of the page, you must tick the first box before downloading:
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105 [[image:Backup_options_en.png]]
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107 See the page [[Backup and Restore>>doc:Digdash.deployment.configuration.backup_restore.WebHome]] for further details.
108
109 == Data Catalog ==
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111 The dependency analysis manager allows you to query a specific element on an ad hoc basis, but you can also generate reports. This enables you to analyse or document entire sections of your environment in the form of tables or graphs, and even use a {{glossaryReference glossaryId="Glossary" entryId="fabrique de documents"}}document builder{{/glossaryReference}}.
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113 To do this**, **you can use data sources of the **‘Data Catalog’ **type. See** **the page [[Connecting to the Data Catalog>>doc:Digdash.user_guide.studio.Create_datamodel.Data_connection.connect_data_catalog.WebHome]] for further details.
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115 [[image:Dependency_data_catalog_en.png]]
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118 In the example above, we are creating a three-column data source: **{{glossaryReference glossaryId="Glossary" entryId="Flux"}}Flow{{/glossaryReference}}**, **Dashboard Page**, **Role**.
119 This enables you to create charts showing the links between flows and **dashboard** pages by role.
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122 Another type of source, more focused **on “documentation”**, could present **measures and data sources** by **role**.
123 By ticking the **“Description”** box for the **Measures **and **Data Sources **columns, you can then create tables explaining the purpose of each metric. As the tables can be filtered by role and data source within the dashboard, navigating this new, customised knowledge base is made easier.