Adding Mashup Data to IT Visibility

Note:If you have already upgraded to Technology Intelligence Platform, information in this section is not applicable to you. The Data Mashup feature will no longer be accessible from the IT Visibility user interface (IT Visibility > Data Mashup) instead use the Contextual Data Store API to augment your organization’s inventory data with non-discoverable business context data you provide.

Adding your data via IT Visibility’s Data Mashup feature requires you to provide a CSV file with a reference column based on (D) Hardware ID, (H) Technopedia GUID, or (S) Technopedia GUID as the key field. During the upload process, IT Visibility also requires you to identify the reference column and, optionally, name the dataset and name the attribute and fact columns.

Reference Field Requirements

The field you use as a reference field depends on how you want to use the mashup data:

(D) Hardware ID (dhardwareid) is the reference field to use for data related to devices.
(H) Technopedia GUID (htechnopediaguid) is the reference field to use for data related to hardware models.
(S) Technopedia GUID (stechnopediaguid) is the reference field to use for data related to software releases.

Important:In the CSV file, a reference field is required, the first row must include column names, and the column name for the reference field must be dhardwareid, htechnopediaguid, or stechnopediaguid.

CSV File Limitations

The following limitations apply to CSV files you upload with your business context data:

CSV files uploaded for data mashup must use UTF-8 encoding.
The values in the CSV file can include only standard English characters; they cannot contain extended, non-standard characters.
The values in the CSV file can include commas, but these values must be enclosed in quotation marks.
The maximum file size for a data mashup CSV file is 1 GB.

If you get an error when you attempt to upload business context data, verify that the file size is under 1 GB, that the values include no non-English or non-standard characters, and that any values that include commas are enclosed in quotation marks.

Tip:To quickly build a CSV file for data mashup, consider creating a report in IT Visibility that includes (D) Hardware ID (dhardwareid), (H) Technopedia GUID (htechnopediaguid), or (S) Technopedia GUID (stechnopediaguid) plus any other data that will help match up the business context data you plan to upload with existing devices, hardware models, or software releases, respectively. Then, save and export that report as a CSV file to use as a starting point to merge with the business context data you intend to upload.

CSV File Data

Depending on the data contained in the CSV file, the column types are populated in the Connect to your existing model dialog box after the CSV file import is successful. There are three column types:

Reference—If the CSV file contains a column with the reference field, such as dhardwareid, htechnopediaguid, or stechnopediaguid, the default column type is Reference.

The CSV file contains the key-value pairs. You can also associate multiple values with the same key. For example, you can associate three different regions such as NAM, EMEA, and APAC with the same htechnopediaguid key (in this case 1a3baafb-1428-4396-8610-bd06f79bca10).

Single Reference Key with Multiple Values

htechnopediaguid

Region

1a3baafb-1428-4396-8610-bd06f79bca10

NAM

1a3baafb-1428-4396-8610-bd06f79bca10

EMEA

1a3baafb-1428-4396-8610-bd06f79bca10

APAC

Attribute—If the CSV file contains a column with non-measurable descriptors (such as name, title, phone) by which you want to break down your data, the default column type is Attribute.
Fact—If the CSV file contains a column with data such as amount or value that you want to measure, the default column type is Fact.

To add mashup data:

1. In Flexera One, click IT Visibility > Data Mashup to open the Data Mashup page.
2. Click Add CSV. The Choose a CSV file dialog box opens.
3. Locate the CSV file you want to upload using the Browse button or drop the CSV file onto the Choose a CSV file dialog box.

Note:The CSV file must contain a column that references an existing dataset such as dhardwareid (for devices), htechnopediaguid (for hardware), or stechnopediaguid (for software).

After the CSV file import is successful, IT Visibility opens the Connect to your existing model dialog box. For more information about the data populated in the Connect to your existing model dialog box, see CSV File Data.

4. In the Connect to your existing model dialog box, you can name the dataset, set the reference, attribute, or fact, and confirm the data structure.
Custom dataset name—Provide a name for the dataset in IT Visibility. The default dataset name is the name of the CSV file you uploaded. After a successful upload, the dataset name appears in Data Explorer as the group name for the data you are uploading.
Reference/Attribute/Fact—For the key column in your CSV file, set the Reference/Attribute/Fact control to Reference and choose Hardware Properties, for device data, Hardware Technopedia, for hardware data, or Software Properties, for software data. For other columns, set Reference/Attribute/Fact to Attribute or Fact and, optionally, enter a different attribute or fact name for those columns.

Important:You can select only one column as Reference.

Confirm Selection—Click Confirm Selection when you are ready to review the data model changes specified in the Connect to your existing model dialog box.

IT Visibility opens the Publish model dialog box when you click Confirm Selection.

5. In the Publish model dialog box, review the data model changes and click Publish.

When IT Visibility completes loading the dataset, it shows the new dataset in the Analytics Enhancements list on the Data Mashup page.

After the new dataset appears on the Data Mashup page, you can find the new data listed in Data Explorer under the name you provided as the Custom dataset name.

For more information about loading new data, updating a dataset’s structure, or deleting a dataset from the Data Mashup page, see Editing Data Mashup Datasets.