Data Flow Analysis

Overview

The Data Flow Analysis tab, found in your Vendor, Services, and Partner detail pages, provides an understanding about the type and nature of your data flows, including the particular APIs, data types, and lineage for specific third-party entities or internal services.

Data on this tab represents your 'operational reality'.

This can be compared with the ‘contractual reality’ from the Contract Analysis tab.

The Data Flow Analysis tab

The Data Flow Analysis tab is comprised of three sections:

1. Top Panel Summary

The top panel presents users with a high-level summary of information about the vendor or service and related data flows.

The summary is geared around 4 primary elements:

• Data Types: The data types discovered by Relyance and associated with the vendor.
• Data Flows: Data flows represent the unique flows from your internal services/components with the vendor. For example, more than one internal service could be connected with the vendor via the source code. The internal services represented here are typically defined in the YAML file during the Source Code Integration. Check out this article for additional information about the Source Code Integration process.
• Services: Services are internal microservices / unique components that represent a logical grouping of your source code. These services are defined in the YAML file during the Source Code Integration process.
• Data Sources: Data Sources represent different sources Relyance discovered a vendor from. On the Data Flow Analysis tab, Relyance displays vendors that get detected from the Source Code or a direct vendor integration.

2. Left Filter Panel

The filter panel allows users to filter by Data Types, Data Flows, and Data Sources.

Use the Filter By dropdown to filter by:

• Data Types: This selection allows users to view all the data types discovered for the entity and filter the data by a specific data type. Users can choose to filter by personal data types, special categories of data, or other data types. You can use the search box to filter this list of Data Types.
• Data Flows: This selection allows users to filter by unique data flows Relyance discovered in relation to the entity.
• Data Sources: This selection allows users to filter by a data source (in cases when there are multiple data sources). The values in this filter allow you to select a specific data source.

By default, this view is filtered on Data Types associated with the vendor on the left-hand side.

When filtering by the different selections, the right-side details panel will update to show the relevant sections.

3. Right Details Panel

This panel lets users dig deeper into the 'operational reality' data that Relyance has found, sorted by different elements based on the filters used in the left panel. Expand each section to get more details about this entity.

The left filter panel will automatically remove the section you're using to filter with from this panel.

Data Types

This section shows a list of Personal Data Types and Special Category of Data types.

Data Flows

The Data Flows section provides you with context of how data flows between the entity and services.

Pay attention to the arrows that show the direction of data flow.

Services

This section lists all the related services found for this entity.

Data Sources

This section provides insight into how this entity was identified. In the example below, this entity was found via Vendor Discovery, Source Code Scan, and the direct Vendor Integration.

Code & API Calls

The Code & API calls table displays the granular lines of code or a REST API integration endpoint along with the data types predicted. This detailed information enables our legal and engineering end-users to collaborate and consume this information.

The checkbox Only Show API Calls with Data Types allows you to quickly identify data type calls in this table.You can use the search box to find a particular file, data type, or language.

4. Data Flow Intelligence

With Data Flow Intelligence, you can gain more context on predictions from Relyance AI by hovering your cursor over a personal data type. This action triggers a contextual pop-up that explains why a specific data type was suggested. Based on the source of the prediction (source code integration, APM integration, vendor integration), the intelligence pop-up displays additional context about the data type prediction. As an end user of Relyance, you can use this context to have conversations with internal stakeholders to take appropriate action on the data flows that Relyance outlines.

Relyance continues to add data flow intelligence support for all integrations we offer. If there is an integration without data flow intelligence support you want us to consider; please work with your Customer Success team.

For data type predictions from your source code analysis, the data flow intelligence pop-up displays the file name, code entity name (variable, function, parameter, etc.), and the line number from the source code that Relyance used to make a prediction.

For data type predictions from vendor integrations, the data flow intelligence pop-up displays the API endpoint name of the SaaS system that Relyance queried and the API endpoint key name (shown as “Column Name”) that Relyance used to make a prediction.

For data type predictions from structured stores (like Snowflake), the data flow intelligence pop-up displays the Table and Database Name, Table Location, and Column name in the table that Relyance used to make a prediction.

For data type predictions from APM integrations (like Datadog), the data flow intelligence pop-up displays metadata about SQL queries in traces that Relyance used to make a prediction.

5. Exporting Data

The Export Data feature enables users to customize and download data from the Data Flow Analysis screen in the Relyance AI platform. You can choose specific columns, apply filters, and select the export format to tailor the output to your needs.

Accessing the Export Feature

1. Navigate to the Data Flow Analysis screen under Vendors (TPRM).
2. Locate the Export button (download icon) in the top-right corner of the screen.
3. Click the Export button to open the Export Data dialog.

Customizing Your Export

The Export Data dialog allows you to customize your export with the following options:

1. Selecting Columns

• You can specify which columns to include in the export.
• To include all columns, check the Select All option. Alternatively, select individual columns based on your requirements.
• Different integration sources (such as source code, APM, or direct API-based connections) provide varying metadata. If you are exporting data from multiple sources, note that certain columns may be blank for specific rows depending on the metadata available from each source.

2. Filters

• If you applied filters on the Data Flow Analysis screen, these will be pre-selected in the Export Data dialog.
• You can modify these filters directly within the dialog if needed, ensuring that only the relevant data is exported.

3. Export Format

• Choose between two available file formats:
  • CSV: Ideal for spreadsheet applications and lightweight data analysis.
  • Excel: Suitable for detailed analysis with rich formatting options.

Generating Export

1. After customizing the options in the dialog:
   • Select the desired columns.
   • Review or adjust the filters.
   • Choose the preferred file format.
2. Click the Generate Export button to initiate the process.
3. Once the export file is ready, a Download File dialog will appear, allowing you to download the file directly. If you close this dialog without downloading the file, you will need to start the export process again by reconfiguring your options.

More Info:

Please see this video article for more information.