Table of Contents

This reference outlines the process to upload new records or update existing records in your Gnosis database, starting from an .xls or .csv format.

Data Preparation

For the best possible upload outcome (minimizing the creation of duplicate records and generally clean record data), data cleaning is required before uploading.

For the system to identify existing records during upload the following must apply:

People - First Name, Last Name, and Email OR Address Line 1 must match 100%

Organizations - Organization Name and Org Address Line 1 must match up 100%

If the Gnosis profile and the upload file have the same address formatted different by even one character or space, a new Gnosis profile would be created.

Data points to review for data cleaning:

  1. Letter case – Review for appropriate capitalization in all necessary fields – all fields upload as is.
  2. Combined persons – One name per Gnosis profile. If the first name is “Adam & Beth”, remove the second person, make a note of it separately, then update/override the HH Name and Salutation once the record base been uploaded to your database. (Although these fields are available in the upload template, depending on the actions selected during upload you could accidentally clear existing HH Name and Salutation data if you include these fields in the template.)
  3. Orgs v. People – Must separate the two sets of data, creating the necessary org name, address, etc. columns for proper upload. You can still upload a personal contact if name and email were given. If formatted correctly, Gnosis would upload the person and the organization, linking the two appropriately.
  4. Address normalization – Rely on SmartyStreets service for each upload or potentially edit addresses manually using Find/Replace.

Template Preparation

Download the Standard Upload Template from Gnosis to compile your data.

  1. Gnosis Process menu > Upload Data icon
  2. Click to download the template:
  3. Read the Introduction tab of this document carefully for instructions.
  4. Two options:

a. Carefully paste data into appropriate columns of the template, OR

b. Paste the necessary columns headings from the template document into your data .xls or .csv.

Outline of Field Sections in Template:

Person fields Columns A-Z

Organization fields Columns AF-AT

*Person’s org-related data if linking to new or existing org record Columns AB-AD

Attributes (any record tab, person or organization) Columns AV…

*If uploading a person and an organization on the same row, the system will link the person record to the organization record.

5. All data elements must be in their own separate columns as identified in the upload template.

6. If necessary, complete any data updates/fixes/alterations in your document before proceeding.

7. When finished, save the file as a Comma Separated Values (.csv) document.


Upload Process

  1. Select the Gnosis Standard Spreadsheet Import option.
  2. Click in the open file text box to locate your saved .csv file.
  3. Load File > your data will load below.
  4. Make any necessary selections (**only used when updating existing records using existing Gnosis OIDs or PIDs)
    1. **Auto Update Missing Data: any new data in the file will be added to existing record
    2. **Auto Update All Data: all data in the file will override existing record data
    3. Disable Duplicate Checking: If all records are NEW, check this box to speed up upload.
    4. Import Keys from FDS: This is a Support only option; do not check this box.
  5. Validate & Import > you will see line by line progress of data import.
  6. IMPORTANT: Immediately following the upload a system prompt will appear asking if you wish to save the log file; always save the log file when importing records. We recommend saving the import log in the same file location as your import .cvs file.

If necessary, you can then use the IDs from this log to mass update other attributes not updated in your data upload, at a later date. See the article on Attributes - Mass Updating & Moving Data for instructions on this process.



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