Data Quality Flashcards
What are the 6 steps toward top data quality?
- Profile your data
- Control your data
- Integrate data
- Augment your data
- Monitor your data
- Assign ownership, train users and commit to a data quality process
Which objects can duplicate management manage?
Business Accounts
Person Accounts
Contacts
Leads
Custom Object records
What is the purpose of matching rules as used by duplicate management?
It is matching criteria to identify duplicate records
Which 3 standard matching rules exist today
- Business Accounts
- Contacts and leads
- Person Accounts
What do duplicate rules do?
Determines actions to take as duplicates are encountered Can alert (or block) a duplicate from being created
Which key attributes can affect data quality?
- Age (when were the records last updated)
- Completeness (Make a list of fields required for each business use. Then, run a report that shows the percentage of blanks for these fields)
- Accuracy (AppExchanges apps for data quality can be used to help determine accuracy against a trusted source)
- Consistency (Reports can show the variations for each true value for a given field)
- Duplication
- Usage
What are some of the questions you can ask (or look at) when looking at how age affects data quality?
How long you have had it for
Is it up to date
For data migration (for new implementations) or bringing in a department / business unit you look at the data they have and how old it is
What to look at when looking at completeness (in terms of data quality)
How many fields are you collecting data for
Are certain fields required at certain points
It can help guide thoughts on how you design it
What to look at when looking at accuracy of your data (in terms of data quality)
Look at the input format (for example phone numbers)
Tools you can use like data.com, onesource, xperian to pull in information on which companies roll up into which records
Contact information that they are accurate and/or correct
You can even get temps to help validate the data
What to look at in consistency (in terms of data quality)
Making sure that all the systems have the same single record of that customer, same telephone number, date of birth
What to look at in duplication (in terms of data quality)
Ensure there are no duplicate records :)
What to look at in Usage (in terms of data quality)
How often is the data used. If it is not used, then what is the point of having (or capturing) it
How can you encourage compliance for your data (example Accounts and Contacts)
Use exception reports and data-quality dashboards to remind users when their Accounts and Contacts are incorrect or incomplete. Scheduling a Dashboard refresh and sending that information to manages is a great way to encourage compliance.
What does a typical Data Management Plan include?
Standards for creating, processing and maintaining data
Name some data standards that can be included on a Data Management Plan?
- Naming Conventions (ex suffixes, abbreviations)
- Formatting (ex dates / money)
- Workflow
- Quality (ability to measure/score records)
- Roles and Ownership
- Security and Permissions
- Monitoring
What are some options to do when implementing your Data Management Plan? (hint: some config or other changes to make in Salesforce)
Use: Required Fields Validation Rules Workflow Rules Page Layouts Dashboards Data Enrichment Tools Duplicate Management Custom Field Types