Subsequent organizational data uploads

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Administrators can use the post-obit steps for a subsequent upload (import) organizational information to Viva Insights in Workplace Analytics. Complete the steps after preparing the information as described in Prepare organizational data.

Important

Only follow these steps if this is not the offset time you accept uploaded organizational data to Workplace Analytics. If this is the offset time, follow the steps in Upload organizational data (kickoff upload).

Import tasks

Importing organizational data requires the following tasks:

  1. File upload
  2. Field mapping
  3. Data validation

After yous prepare the source information, you lot can upload the .csv file and map fields. After y'all map fields, Workplace Analytics validates the data. When the data successfully validates, the overall data-import task is complete. If the data validation is non successful, you tin choose from a few options that are described in Validation fails.

File upload

Utilize the following steps to upload (import) your organizational data as a .csv file into Workplace Analytics.

To select the file to upload

  1. Open Workplace Analytics. If prompted, enter your organizational credentials.

  2. Select Data sources > Organizational information.

  3. Select Upload to run into your organization's Upload history, and and so select New upload.

  4. In Upload, select Proper noun your upload, enter a proper noun, select Add an optional clarification, and and then enter a description.

  5. In Select file, choose Select file, select the .csv file with the new employee data you want to upload, and so select Open up after reviewing the following important upload considerations:

    • The .csv file that you upload must be UTF-8 encoded.
    • Brand certain that the file you are uploading is not open in a different programme when you begin the upload process.
    • Subsequently the upload process begins, the process is irreversible.

    Note

    If you are uploading new data, go to pace 8, Complete new file upload. However, if you have uploaded data and then discovered that it contains sensitive, incorrect, or unauthorized data, you lot must remove the uploaded data and supervene upon information technology with a new file. To practice this, become to step 9, Append or supersede organizational data.

  6. To complete a new-file upload, select Adjacent. This shows the System fields table. Go to Field mapping.

  7. If you are not uploading a new data file, y'all must now cull whether to append or replace organizational data. In the Suspend or replace area, select one of the following options:

    • Employ Append the existing organization data to update attribute values for existing employees, to add together new employees, or to add new attributes (columns). This is the default pick.

    • Use Replace all existing organizational data with this file to delete all previous HR data uploads, so that the data in the current upload becomes the only 60 minutes data that is present for your organization in Workplace Analytics. Take notation of the "Circumspection" message, which explains that this supervene upon choice permanently deletes all previously uploaded organizational information.

    Later you take called to suspend or to supercede data, select Next and become to Field mapping.

Field mapping

You need to map the fields (columns) for the source .csv file to the field names that Workplace Analytics recognizes. You map these in Organizational data > Upload.

New upload field mapping

The Upload page includes tables for Organisation fields and Custom fields for mapping the data for the upload file.

When appending new attributes to an existing upload, yous need to select notwithstanding required and optional attributes that you lot mapped before in previous uploads, in addition to the new attributes yous want to add (append).

System fields table

System fields correspond attributes that are known by Workplace Analytics and are used in specific calculations across grouping and filtering. A arrangement field tin can be either required or optional. Notwithstanding, the validity threshold cannot be changed when editing existing data.

  • Required fields are identified in two ways. Their rows have nighttime shading and show as "Required" under the Source column header. These rows stand for data that was found in the uploaded file. For the upload to succeed, y'all must map the required fields with a column in your .csv file that is the correct data type and meets the validity threshold.

    Important

    Every required field must have a valid, non-nix value in every row. This means that, even if the names of these attributes are not present in the uploaded .csv file, other columns must be present in the .csv file that are mapped to these attributes.

  • Optional fields appear below the required fields in rows that have lighter shading. These rows are unremarkably encountered system fields that Workplace Analytics suggests for utilise. You don't need to map these fields if your organization doesn't accept data for them.

Custom fields table

  • Custom fields announced on this page beneath the optional fields. Custom fields are optional attributes you tin can create. Select a column from your source.csv file. Name the column, select the data type, set the validity threshold, and and then select the report option.

Field cavalcade details

  • Source column corresponds to each of the fields in the uploaded file.

  • Workplace Analytics proper name is the name of your organization'southward Workplace Analytics.

  • Information type is the data type of the fields.

    Annotation

    If the information blazon is Boolean, the value for the Boolean field must exist TRUE or Simulated.

  • Validity threshold sets the pct of rows in the uploaded file that must accept non-null values (no blanks) for the attribute. The source file might still be valid fifty-fifty if some rows have missing values for some columns. This setting is not intended to check or let invalid values. A single invalid value, such as an incorrect information blazon, email address, or TimeZone string will cause the file upload to fail. The following summarizes the threshold settings:

    • Required attributes - Considering PersonId and EffectiveDate are required attributes, their Validity threshold value must be 100 percent. This value cannot exist changed.
    • Fields with minimum values - The threshold for the ManagerId, Arrangement, and LevelDesignation fields is set to 95 percent past default.
    • Other organization fields - The Validation threshold for other system fields is set to 95 percent by default, but y'all can increase or decrease this value.
    • Custom fields - See Ready Validity threshold for custom fields.

  • Include in report lets you decide how to care for sensitive information in the report that will exist generated almost the import operation. The following options are bachelor for each of the columns in your source data:

    Map data fields.

    • Evidence in written report - Lets the bodily data value appear in the study simply every bit it was imported in the organizational data file.
    • Hash in written report - De-identifies sensitive data. If you choose this option, the written report will include data that was generated about the import functioning, but instead of showing actual values that were taken from the source file, it shows a hashed version of the value – a format that cannot exist read.
    • Exclude from report - Prevents the data value from appearing in the written report. You tin can select this option for any attribute that y'all consider highly sensitive. However, for data-privacy reasons, Workplace Analytics automatically assigns Exclude from study to item attributes, such as ManagerID. In those cases, you cannot modify this value.

    Note

    The visibility of one or more than attributes (columns) might be set to Evidence in report or Hash in report for previously uploaded data. If you modify this setting to Exclude from report, any auto-refresh query that depends on the data in that cavalcade volition experience a schema violation.

    In this example, after you finish mapping fields, Workplace Analytics shows a alert message that reads "Your upload has certain issues that may affect execution of the auto-refresh queries." If you see this message, go to If expected columns are missing or excluded.

To map fields

After you consummate the steps in File upload, the Upload folio with the System fields tabular array will appear.

  1. Map the required fields.

    1. Determine which of the columns in your .csv file represent to the second column in the table (Workplace Analytics proper name).
    2. Under Source column, select the downwardly arrow to come across the listing of the columns in your .csv file. From the listing, select the right cavalcade name for this data.
    3. Fix the appropriate values for the other columns in the table, such as the Workplace Analytics proper name, Data blazon, and so on. Repeat these mapping steps for the rest of the required fields.

    Note

    For more data, see Field column details.

  2. Map the optional and custom fields, as applicable. You simply demand to map the columns in your source (.csv) file that your organization considers important for analysis. For example, if "Region" is important and your information contains this field, map it.

    Map custom system fields.

    1. Under Source cavalcade (the first column in the tabular array), select the downward pointer to run across the list of column names that were found in the data file. From the list, select the column proper noun for the data. In this example, you'd select the source column for Region.
    2. Set values for the other columns in the table, such as the validity threshold and study options.
    3. Repeat these steps for all optional and custom fields that are important to your organization.

  3. In the Submit for validation area, select I confirm that these mappings are correct, and then select Submit. This uploads the data file and starts the validation process.

  1. After you select Submit, two circumstances could trigger a alert message:

    • Omitted columns - If (a) You lot chose the Replace option for uploading organizational data, and (b) while mapping fields, yous take chosen to omit one or more columns that are present in the existing organizational-data schema, and (c) at to the lowest degree one motorcar-refresh query depends on those (omitted) columns.

    • Excluded columns - If (a) While setting the Report options for attributes on the Mapping folio, yous accept chosen to exclude i or more than columns from query results, and (b) at to the lowest degree one auto-refresh query depends on those (excluded) columns.

    In either instance, Workplace Analytics shows a warning message about problems that could bear upon auto-refresh queries. If you see this message, become to the section If expected columns are missing or excluded. If you exercise not see this alert bulletin, become to the adjacent phase, Data validation.

If expected columns are missing or excluded

For a query to run successfully, information technology requires particular attributes (columns) to be present in the organizational data. This is likewise truthful for queries for which the auto-refresh option is turned on. If expected columns are missing, or if visibility settings (which you lot set by using the Report options on the Mapping page) exclude expected columns, Workplace Analytics shows a warning message:

auto-refresh query warning.

Below this message, a table in the Warning details surface area lists the affected auto-refresh queries and provides details about problems that were encountered. This information is for review just. Yous cannot modify data or mapping settings on this page.

After you review the issues, if you decide not to continue with the data replacement, select Back. This returns yous to the field mapping folio; continue with the steps in To map fields.

To continue with data upload despite the issues, select Next. Note that this choice will turn machine-refresh off for queries that were listed in the Warning Details area. The results of the last runs of these queries remain available.

Information validation

After you complete the steps in Field mapping, the organizational data file is uploaded and validated, and the Upload page shows the File is being uploaded screen:

Upload in progress.

In most cases, file validation should complete very quickly. If your organizational data file is very large, validation could have up to ane or 2 minutes.

Afterwards this phase completes, the file has either passed or failed validation. Get to the appropriate section:

Validation succeeds

Validation fails

Annotation

Each tenant can have merely one upload in progress at a time. Therefore you need to complete the workflow of one data file, which means yous either guide it to a successful validation or carelessness information technology, before yous brainstorm the workflow of the side by side data file. The status or stage of the upload workflow is shown on the progress bar beyond the superlative of the Upload folio.

Important

You must stay logged in while the file is uploading or the upload will be canceled. The upload requires this page to be open in your spider web browser during the upload. If you close the browser (or this browser page), the upload will fail.

Validation succeeds

If validation succeeds, the Upload page volition betoken it and show the size of the upload and that the overall process is complete. Later on successful validation, Workplace Analytics processes your new data.

Validation succeeded.

You tin can select Settings > Upload > Organizational information to see Upload history. Y'all can then select Successes to come across the workflows that were successfully validated (and uploaded).

You can practise the following for an upload:

  • Select the View (eye) icon to meet a summary of the validation results.
  • Select the Mapping icon to run across the mapping settings for the workflow.
  • Select the Download log icon to run into the log.

Annotation

Each tenant tin accept only one upload in progress at a fourth dimension. Therefore you need to complete the workflow of one data file, which means you either guide it to a successful validation or abandon it, earlier you begin the workflow of the adjacent information file. The condition or stage of the upload workflow is shown on the progress bar across the top of the Upload page.

Validation fails

If information validation fails, the Validation folio shows a "Validation failed" notification. Information technology too shows details nigh the validation attempt and presents yous with options:

Validation failed.

After a failed validation, it'due south best to offset gain an agreement of the errors by scanning the mistake summary tabular array. You can also select Download problems to examine the error log.

This information about the errors helps y'all decide which path to choose side by side — whether to fix the source information, change the mapping, or abandon the electric current upload. The following describes these options:

Options upon failed validation

Nature of errors Recommended selection Description
Small-scale errors, small in number Select Edit mapping This displays the Field Mapping folio, on which you tin change how you map source-file fields to Workplace Analytics attributes, optionally change validation thresholds, and then re-attempt validation. Y'all can exercise these things without changing and re-uploading the source file. This is all-time for pocket-sized errors such as having mapped the wrong cavalcade in the source file or assigned a too-loftier validation threshold to a item attribute.
Major errors Select Upload file This displays the first File upload page. Consider this option in the example of major errors in the originally uploaded information. First, edit the source-information file to fix those errors and then re-attempt the upload and validation process with the corrected file.

In that location is besides an selection to select Abandon, a button on the acme right of the page. Select this to cancel the current upload. Yous can carelessness your upload for any reason, related or unrelated to errors in the upload file.

Note

  • Workplace Analytics does not alter or fill in data that is missing from HR uploads, such as for TimeZone. The administrator is responsible for correcting such errors or omissions.
  • When whatever data row or column has an invalid value for whatever attribute, the entire upload will neglect until the source file is fixed (or the mapping changes the validation type of the attribute in a manner that makes the value valid). Lowering a threshold does not ignore or skip an invalid value.

The following can help correct data in an uploaded source file that might be causing the validation errors.

When any information row or cavalcade has an invalid value for any attribute, the entire upload will fail until the source file is fixed (or the mapping changes the validation type of the aspect in a mode that makes the value valid). Lowering a threshold does not ignore or skip an invalid value.

Rules for field headers

All field header or column names must:

  • Brainstorm with a letter of the alphabet (non a number)
  • Only incorporate alphanumeric characters (letters and numbers, for example Date1)
  • Have at least 1 lower-case letter (Hrbp); all capital letter won't work (HRBP)
  • Match exactly as listed for Workplace Analytics' Required and Reserved optional attributes, including for example sensitivity, such equally PersonId and HireDate
  • Have no leading or trailing blank spaces or special characters (not-alphanumeric, such as @, #, %, &); if spaces or special characters are included, Workplace Analytics will remove them from the name

Rules for field values

The field values in data rows must comply with the post-obit formatting rules:

  • The required EffectiveDate and HireDate field values must be in the MM/DD/YYYY format
  • The required PersonId and ManagerId field values must be a valid email address (for instance, gc@contoso.com)
  • The required TimeZone field values must be in a supported Windows format
  • The required Layer field values must contain numbers only
  • The required HourlyRate field values must contain numbers just, which Workplace Analytics assumes is in U.s. dollars for calculations and data assay

Note

Workplace Analytics does not currently perform currency conversions for HourlyRate data. All calculations and data assay in Workplace Analytics presume the data to be in US dollars.

Rules for characters in field values

The following field rules apply to characters in field values:

  • Double-byte characters, such as Japanese characters, are permitted in the field values

  • Limit the graphic symbol length of field values in rows to a maximum of 128 KB, which is about 1024 x 128 characters

  • The following characters are non permitted in field values:

    • tilde (~)
    • "new line" (\northward)
    • Double quotes (" ")
    • Single quotes (' ')

Improver of a new data cavalcade

Permit'south say that you've already uploaded at least 13 months of snapshot information, which independent the five required columns (PersonId, EffectiveDate, LevelDesignation, ManagerId, Organization) for all employees. At present, you want to upload i new cavalcade of data – for instance, an date score value for each employee – and you lot want it to employ to all of the historical data. When you upload to suspend the new "EngagementScore" data column, remember to re-upload all five of the minimum required fields along with the new field.

Set Validity threshold for custom fields

The threshold checks for non-nada values, and then it depends on the intended use of the custom field. If yous intend to use this data in much of your analysis, consider setting it to a high pct. You lot can set a lower threshold for data that applies, for example, to merely a minor subset of people in your organization.

Ready a high value

Generally, you should set up the Validity threshold to a loftier value. This is particularly important if your analysis will focus on that field.

For example, you might include a "SupervisorIndicator" attribute. At offset, you lot might not think that you're analyzing manager behavior and you might exist tempted to omit this attribute. But the system hierarchy is used implicitly by many Workplace Analytics analyses – for differentiating unlike work groups, for determining high- and low-quality meetings based on how many levels attend, and more than.

Set a lower value

The goal of your analysis might be to determine sales effectiveness. Your data might include an attribute for sales attainment that only makes sense for members of your sales strength, who constitute about 10 per centum of the company. This number doesn't apply to engineers or program managers, just it is critical for high-performers in sales.

  • Prepare organizational information
  • First upload of organizational data