Analytics Dashboard Implementation19% of the exam

Compare table windowing and SAQL time series

The compare table's window functions and the SAQL they generate: row ranges, reset groups and ordering rules, rank versus dense rank, period-over-period grouping, and forecasting with fill and timeseries, including its licence requirement.

Official exam objective
Given business requirements, use advanced functionality such as windowing and time series analysis within compare tables.

~7 min read · 8 practice questions ·

What the exam expects

  • Pick the compare table function (Sliding Window, Percentage of Group, Rank Within Group, Period Over Period, Change from Previous, Running Total) from a business requirement, with the right reset group.
  • Read and write SAQL windowing: row ranges, partition by, order by, and the rules that make an expression invalid.
  • Predict ranking results with ties for rank(), dense_rank(), cume_dist() and row_number().
  • Forecast with timeseries, preparing gaps with fill, handling a partial last period, and knowing what an org without the right licence gets back.

Key terms: compare table (a lens table whose columns hold formulas and window functions on measures); window function (an aggregate over a range of adjacent groups that doesn't change the row count); row range (the window, such as [-2 .. 0]); reset group (partition by columns that restart the calculation); timeseries (the SAQL statement that predicts future data points).

Key facts

Windowing and row count
Detail
Doesn't change the number of rows returned
[..] with sum, avg, min or max
Detail
order by not allowed
Ungrouped query
Detail
Windowing not available
partition by all
Detail
No reset boundaries
Period Over Period
Detail
Group by year first; compound dates allowed
Formula columns
Detail
Can't be filtered
timeseries licence
Detail
Growth or Plus for full results; otherwise 1 forecast period
timeseries position
Detail
After a projection statement
ignoreLast default
Detail
false
predictionInterval
Detail
80 or 95
Seasonal monthly model
Detail
At least 24 data points
Pivot table
Detail
Last grouping sets the columns; cells show the first measure
fill gaps
Detail
Adds missing periods with null values
Sources for this section (6)
  • Why doesn't adding a window column change a table's row count?
  • When must a compare table formula use raw field names instead of A, B, C?
  • What does timeseries return when it receives no data?
  • When does fill ignore its startDate and endDate?

The questions are free to read. Answers with their sources and self-grading are included with the pack.

Keep reading with the CRM Analytics and Einstein Discovery Consultant pack

  • Core concepts
  • Exam traps
  • Worked scenario

The pack includes:

  • All 26 lessons of the CRM Analytics and Einstein Discovery Consultant guide, with reading progress
  • Interactive decision walks and step-by-step sequence steppers
  • Practice exams purchase adds inline bank questions and topic practice (8 questions for this lesson)
  • An official source cited for every claim
  • An AI tutor that answers from the guide
  • Choose guide-only, practice-only, or save $4 with both

Practice for the CRM Analytics and Einstein Discovery Consultant exam