Analyzing impact analysis for apps, scripts, and datasets

Impact analysis shows the forward-looking, downstream view of a database, app, or field dependencies. It answers questions about which databases, apps, files, links, and other resources would directly or indirectly be impacted if the value of a field changes. You can also drill down to the particular fields that are impacted by the change.

Qlik Cloud provides an aggregated summary of downstream impact where you can interactively examine direct and indirect dependencies of a given field or object.

Downstream lineage is called impact analysis because it analyzes which objects will be impacted by changes to your data or application; these objects are the dependents of the base node. Qlik Cloud provides information and counts by type of dependent objects in a summary view.

Business users examining a given field will have an aggregated summary of downstream impact that delivers insight into:

• Which object types would be impacted by a change to this field including databases, file storage, apps, and links
• Which Power BI reports and dashboards would be impacted
• Which Qlik NPrinting reports would be impacted
• Which data models for Power BI and Tableau would be impacted
• What is the number of direct dependencies and indirect dependencies by type
• Who are the owners of the items that are impacted if you make a change

To view upstream lineage information such as inputs, transformations, and other historical information that can explain where your data came from and what operations have acted upon it, view its lineage. See Analyzing lineage for apps, scripts, and datasets.

Impact analysis summary view

Open impact analysis by selecting on an app or dataset tile or row depending on your view, and then selecting Impact analysis. You can also access an impact analysis summary view from the overview of a dataset by selecting and then selecting Impact analysis. You can access lineage (upstream) or impact analysis (downstream) for other nodes that appear in graphs by selecting and then selecting Lineage (Use as new base node) or Impact analysis.

In the summary view, you can filter on whether to display all or only direct dependencies. An example of a direct dependency is an app Application A that loads a particular dataset Datafile B. In this case, Application A directly depends upon Datafile B. An example of an indirect dependency is a QVD C.qvd that is created by Application A, based on Datafile B. In this case, C.qvd is an indirect dependency of Datafile B.

The base node being analyzed is outlined in blue. The dependents are listed in the left-hand overview with counts per type. When in focus and listed in the main grid, that type is outlined in a green box. Types of dependencies include databases, apps, file storage, databases, and links. The listed dependent objects for that type are listed in the main grid. Drill into these objects by selecting the row. For example, an app will drill down into table and then field-level.

• Details (see Node details)

• Make this the base node

• Go to lineage (for that object)

• Open to view the metadata Overview for that object. See Dataset overview

Select on the row of the dependent object in focus to access a menu with the following actions:

Permissions

Users without view permission will not be able to view dependent resource names, the Last reload column for dependent apps or the Last modified column for other resource types. Users without view permissions will also not be able to view the context menu or drill-in options for the resource.

Example use case for analyzing impact analysis

For a walk-through of the following example, see:

Impact analysis use cases

The impact analysis summary indicates that this dataset has 5 dependencies: the dataset is used in 4 apps (6 tables total) and 1 file storage (2 QVDs). The QVDs in the file storage are indirect dependencies because they are generated from the apps that were loaded with the base node Sales data.xlsx. Expand the base node Sales data.xlsx which opens a list of fields and select the field Price , now making Price the base node to be analyzed for impact analysis. The listed dependencies decrease resulting in a total of 3 apps that would be affected by a change to the field Price.

The following needs to be addressed:

1. The dataset Sales data.xlsx should be reloaded when the field Price is removed.
2. The owners of the dependent apps Sales analysis and Extract should be contacted so that they know to reload the dataset to their app. Locate the owner from the column Owner or select to open the context menu on the rows of both dependent apps Sales analysis and Extract; select Details to list the owner of the app.
3. The owner of the impacted apps should be contacted and informed that their apps should be reloaded with the modified Sales data.xlsx dataset.