4 Ways to Ensure Data Quality in Blackbaud eTapestry
Data entry is the critical front-end component to good reporting and a healthy Blackbaud® eTapestry® database.
That’s because a mistake during data entry can lead to a whole host of reporting and communications challenges, including transactions not showing up on your financial reports, donors not receiving acknowledgement letters (or not receiving the “right” one), and constituents with new addresses continuing to be mailed at old addresses.
As an eTapestry database administrator, it is important to put in place data quality controls that double check the data entry of your users and the data entry of integrations like web forms and imports.
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Even if you trust your users to enter data accurately, we are all human and sometimes we make mistakes. And even if you’ve set up integrations to enter data correctly, integrations are never perfect and it’s important to keep an eye on how they create data in your database.
Data quality reviews in eTapestry software
Implement data quality control checks on a set schedule so they become a consistent, recurring database procedure. While these quality control checks take time, you will ultimately be saving your organization considerable time and anxiety in the long run by staying in front of data quality issues and ensuring ongoing clean data, accurate reports, and consistent information.
1. Duplicate Report
Good data quality means minimizing the number of duplicate accounts in your eTapestry database.
There are several ways duplicate accounts can be created in your database.
Reduce the number of duplicate accounts created by your users by instituting a “search first” policy at your organization. Train your users to check and make sure that the account they want to create doesn’t already exist in the database before they create a new account.
Unfortunately, there is no blanket policy that can reduce the number of duplicates created by your online form integrations or imports.
Catch and merge duplicate accounts by running the duplicate report on a monthly or quarterly basis and cleaning up all duplicates listed.
Find the duplicate report in the “Reports” dropdown under “eTapestry Standard Reports.” Run the duplicate report with the “Base – All Accounts” query for a global look at your database. Review the duplicate report and determine whether to merge accounts or leave them alone.
The amount of time required to run the duplicate report and merge duplicates is dependent on the number of duplicates in your database, but if you institute a “search first” policy and clean up duplicates on a monthly basis, this process shouldn’t take more than thirty minutes per month.
2. Account Completion Report
It is always painful to pull reports for a newsletter, mailing, or event invitation only to find that a percentage of the accounts in your database don’t have addresses, some don’t have salutations, and others don’t have email addresses. Keeping complete account information is key to a healthy eTapestry database.
Accounts are only valuable to your organization if they are complete. If they aren’t complete, your organization is very limited in the marketing and fundraising activities it can implement.
In order to maintain complete account information, run monthly account completion reports. Run the report with a query that only returns accounts or constituents that were created in the past month. Review the account data—including all required fields—, find gaps in the data, and then go back to each account and complete the account manually (or update them via an import).
3. Transactions Created Last Month Report
It is best practice to make fields like Fund, Campaign, and Approach required for transactions. However, even when they are required fields, it is still important to review your data and make sure that users are associating the right Funds, Campaigns, and Approaches to each transaction. These three categories are critical to good transaction reporting, and it is very easy for a user to accidentally select the wrong value in each of these fields.
Set up a monthly report procedure to review all transactions created last month for key transaction data that, if incorrect, would impact your financials, your follow up with donors, or your fundraising reports.
If you run a similar report with a query like “All Journal Entries Created Last Month” you can skim through and make sure that other journal entries, not just transactions, were entered properly as well. With this query, you can transform your “Transaction” data quality check into a full “Journal” quality control check. Conduct this data quality review on a weekly (with all transactions created last week) or a monthly basis, depending on the volume of transactions at your organization.
4. Online Form Submission Report
If you use DIY, eCommerce, or eCart online forms that add data directly to your database, it is important to implement a data quality check to confirm that data submitted by the form is recorded correctly on the matched account in eTapestry.
Online form submissions will never overwrite existing data in an account, so it’s important to review any fields that should have been populated by an online form against the actual data submitted by the form to ensure all data was entered correctly.
Set up a report that displays all fields included on the online form and the submission data found in the journal entry note automatically created when a form matches an existing account in your database. Run the online form submission report with a query of all eCommerce or eCart journal entry notes.
Look through the report to confirm that form submission data has been matched to the correct account and that all differences between the submitted data and the existing account data have been entered on the account.
Conduct this data quality review on a weekly or monthly basis, depending on the volume of form submissions your organization receives.
Other ways to review data quality in eTapestry
If you are tracking other data in eTapestry like volunteers, grants, memberships, or events, we recommend running data quality reports on a set schedule for those as well. You can use the structures offered in the prior examples to create queries and reports for other checks. Consider scheduling your data quality reports to run automatically to your email in order to prompt your regular reviews.
Managing the consistency, quality, and accuracy of data is critical. These four data quality checks are the foundation of high quality data in Blackbaud eTapestry.
Data management is a difficult task, but simple processes conducted on a consistent schedule can help you manage the complexities of data quality. More importantly, these quality checks can help you generate cleaner reports and exports, which are the ultimate outcome of good data management.
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