Work in Progress
This article addresses the following topics:
- What are question stories?
- Implementing a question story on an agile/Scrum team
- Implementing a question story on a continuous delivery team
- The implementation activities
1. What Are Question Stories?
A question story
is a specialized user story specific to data-oriented requirements.
A question story should be small and ideally implementable within a few hours or days
by the person(s) taking on the work.
The following are examples of question stories:
- As a sales manager I want to know the level of sales by my team by the end of each day so that I know where we stand.
- As an instructor I want to know the certification pass rate of my students so that I can update my seminar marketing message.
- As a restaurant owner I want to know the common combinations of menu options being ordered so that I can identify potential specials.
- As a city councilor I want to know the number of complaints about road quality so that I can determine where we need to focus our repair efforts.
2. Implementing a Question Story on an Agile/Scrum Team
Lets consider the case when a team is following a
Scrum lifecycle.
Figure 1 overviews
an agile project lifecycle, although it is possible for this lifecycle to evolve
into more of a continuous delivery lifecycle where sprint 0 disappears because it
occurred in the distant past and the deploy phase disappears as the result of automation.
Either way, the following advice still pertains.
Figure 1. The Agile Project Lifecycle (click to enlarge).
Figure 2 depicts the
look-ahead data analysis
work required for three
question stories
that are to be implemented during sprint #9 of an
agile DW/BI initiative.
Notice how each question story requires a different amount of data analysis effort due to the fact
that every question has unique data needs.
Figure 2. Look-ahead data analysis on an agile team. Click to enlarge.
Figure 3 depicts the overall development effort
for a single question story, including both the look-ahead analysis required
for the data analytics as well as the
implementation portion called out in Figure 2.
Figure 3. Implementing a question story on a Scrum team (click to enlarge).
3. Implementing a Question Story on a Continuous Delivery Team
Now lets consider the situation when a team team is following a
continuous delivery lifecycle.
Figure 4. A Lean Continuous Delivery Lifecycle (click to enlarge).
Figure 5 depicts the look-ahead data analyis work for the same three question stories
from Figure 2, the difference being that the work is done on
a just-in-time (JIT) basis rather than scheduled into fixed-length sprints. Note that the same amount
of data analysis is still required for each user story as in Figure 2, but that the implementation
time is no longer tied to a two-week sprint.
Figure 5. Look-ahead data analysis on a continuous delivery team. Click to enlarge.
Figure 6 depicts the overall development effort
for a single question story, including both the look-ahead analysis as well as the
implementation portion called out in Figure 5.
Figure 6. Implementing a question story on a continuous delivery team (click to enlarge).
4. The Implementation Activities
As you saw in Figure 2 and Figure 4
there are several activies that the two flows have in common:
- Data analytics - Explore question.
- Data analytics - Explore data source(s).
- Data analytics - Build answer prototype.
- Data analytics - Validate answer.
- Specify answer (Agile/Scrum only).
- Review specification (Agile/Scrum only). Against DoR.
- Implement answer.
- Deploy answer. On a Scrum team you are likely to batch up several answer implementations, whereas on a CD team you hopefully deploy once the answer is ready to be released.
5. Related Resources
