Most of the examples from the courses I’ve watched utilize a dataset where each record represents a “unique” transaction.
I have an issue where I’m charting pipeline progression (movement of records through sales stages) and need to demonstrate weekly progression of existing, or net-new, records.
Therefore, my weekly import “may” contain records that are new (timestamped this week), or existing where some key metric I’m tracking may have changed (could be 1 or more columns of data that have changed for an existing record).
I’ve come up with an idea of creating an update process where I “signal” via a new column, the last know occurence of a record:
PSEUDO CODE:
Latest_Record =
VAR CurrentOPID = CRM_Data[OPID]
VAR CurrentDate = CRM_Data[IMPRTDATE]
RETURN
IF(
COUNTROWS(
FILTER(
CRM_Data,
CRM_Data[OPID] = CurrentOPID &&
CRM_Data[IMPRTDATE] > CurrentDate
)
) = 0,
1,
0
)
QUESTION: Is my logic sound enough to handle various measures like the ones below?
If I have this data, for example:
IMPRTDATE; OPDATE; OPID; GROSS_PROFIT; SALES_STAGE
05/01/2024; 05/01/2024; 12345; $50,000; Working
05/08/2024; 05/01/2024; 12345; $50,000; Working
05/15/2024; 05/01/2024; 12345; $50,000; Qualifying
05/23/2024; 05/01/2024; 12345; $48,000; Qualifying
05/30/2024; 05/01/2024; 12345; $48,000; Qualifying
06/05/2024; 05/01/2024; 12345; $42,000; Decision Due
A) The SUM of Gross profit for this account, in May, should be $48,000;
B) The SUM of Gross Profit for the account, in June, should be $42,000;
C) The cumulative SUM of Gross Profit for this account, to date, should be $42,000
D) The cumulate count of records for this account, to date, should be 1
E) The net-new count of this account, in May, should be 1 (OPDATE==May)
F) The net-new count of this account, in June, should 0 (OPDATE==May)
G) This-Month versus Last Month count should be 0 for June and 1 for May
Any help / advise is tremendougly appreciated.