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Data Questions to Consider

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Before doing an IT implementation or, even better, before going out for proposals, the Data Governance and Support Office would like to suggest the following questions to consider. Think of these as the 鈥渄ata requirements鈥� to complement the 鈥渇unctional requirements鈥� and 鈥渢echnical requirements鈥� that are usually gathered as part of a project. It will be very helpful to be able to assess whether an application will meet your data needs aside from the business requirements.

Questions? Suggestions? Let us know.

Title Question Category
1 Data capture Does a central repository exist for this type of data? Or are the data captured in spreadsheets or shadow systems? Data collection
2 Data entry How do data need to be entered/updated?聽 Bulk upload? Integration? User entry? Data collection
3 Duplicate values Is there a potential for duplicate data entries? How do you reconcile duplicates? Data integrity
4 Data Cleanup Does the data have to be evaluated or cleansed for accuracy? How does that need to be done? Data integrity
5 Data validation Is there a data validation process? Will a data validation process be necessary? Data Integrity
6 Data Retention Does data ever get archived or removed from the system? How long must you keep the data? Data Integrity
7 Unique IDs What unique identifiers exist for these data? How is this unique identifier generated? (Is it a sequential reference ID or combination of data attributes? Is there a naming convention or logic associated?) Data Integrity
8 Unique ID reuse Are unique identifiers ever reused? Why? Data Integrity
9 Error handling Do you have/will you require a process for handling data errors? If so, describe the process? Data Integrity
10 Updating the data Do you have / will you require a data update control process? Data integrity
11 Data migration If adopting a new system, what data will migrate into the new system?

  1. Historical Data
  2. Current Data
  3. New Data
  4. All of the above
 Data Migration
12 Data permissions Do you have / will you require a data sharing control process? What workflow is necessary to support that process? Access Management
13 Data Structure How does the data need to be structured and presented for analysis (longitudinal, cross sectional, fiscal snapshot)? Analytics
14 Frequency/ Timing How readily available does the data need to be to meet the needs of the business (e.g. real-time, end of period, once a year)? Analytics
15 Basis of observation What is the basis of observation (person, object, task)? What is the focal point of the data? Data structure
16 Missing Values How do you treat missing values? Data structure
17 Metadata requirements What information about the data do you have or want? Descriptive (such as keywords, helps people find things), structural (such as relationships, helps people understand how things are organized) or administrative (such as update dates, helps people understand how things are processed)? Data structure
18 Data harmonization Is there data manipulation required to make the data compatible across systems? Where can/should that be done? System Requirements
19 System Restrictions Are there any system restriction for downstream systems that we will have to accommodate? System Requirements
20 Definitions Do you have documented definitions? Data quality
21 Quality dimensions What components of data quality are most important to you?

  • Availability
  • Uniqueness
 Data Quality
22 Provenance Are these data the authoritative source for the information?聽 For all elements or a subset? If not, what is the authoritative source? Data Quality
23 Data Familiarity What is the level of data familiarity of our end users? Do they use spreadsheets? Are they comfortable with having access to the database and creating queries? Do they have experience with ad hoc reporting and selecting criteria to create custom reports? Does the user just want to push a button that extracts the data in the necessary format? Use