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Saturday, April 27, 2019

Einstein Analytics: Handling null values

This blog is not related to Null Handling in Measures. As per this article, null values in Dimensions are not completely supported in Einstein Analytics, however, we often deal with null values in many scenarios.

To prevent data quality issues, Einstein Analytics will disregard any fields in Salesforce (or columns in external data) that are entirely null.

Grouping with Null
Date field by default is null, when you use it in a chart for grouping, null value will not be shown. To overcome this, if you pull data from Salesforce, use defaultValue (e.g. 1900-01-01) to override in sfdcDigest.



Dimension field by default is null, when you use it in a chart for grouping, null value will not be shown. To overcome this, if you pull data from Salesforce, use defaultValue (e.g. NA, " is not needed) to override in sfdcDigest.

Measure field by default will become 0 for null value. We cannot use Measure field for grouping, but we can use it for filter.

Dataflow
If you need to filter out null value for Dimension, you can't use the following in Filter node:
  Field1__c != "" && Field__c != "" <-- this will not filter any
  Field1__c is not null && Field2__c is not null <-- this will throw error

Solution: use defaultValue in sfdcDigest (e.g. NULL, " is not needed) to override null.
so, your filter nodes would be Field1__c != "NULL" && Field2__c != "NULL"
2nd option, adding compute expression nodes to check case when Field1__c is null then "No" else "yes" end, then use Filter nodes to check compute expression field for "Yes".


Filter null records in SAQL
q = load "DTC_Opportunity_SAMPLE";
q = foreach q generate 'Account_Owner' as 'Account_Owner', 'Product_Name' as 'Product_Name', (case when 'Product_Name' is null then "" else 'Product_Name' end) as 'PM';
q = filter q by PM == "";
q = order q by 'Account_Owner';
q = limit q 10;

Count Not null records in SAQL
q = load "Lead";
q = foreach q generate (case when 'SFDC_Lead_ID__c' is null then "" else 'SFDC_Lead_ID__c' end) as 'SFDC_Lead_ID__c';
q = filter q by 'SFDC_Lead_ID__c' != "";
q = group q by all;
q = foreach q generate count() as 'count';

To group null as NA
q = load "DTC_Opportunity_SAMPLE";
q = foreach q generate coalesce('Product_Name',"NA") as 'Product_Name', count() as count ;
q = group q by 'Product_Name';
q = foreach q generate 'Product_Name' as 'Product_Name', count() as count;
q = order q by count desc;


Augment transformation cannot find the parent will cause Null


SAQL Expression in above computeExpression case when 'Acq.Industry__c' is null then "Parent not available" else 'Acq.Industry__c' end

Data in Salesforce

Result in Einstein Analytics

Notes from above screenshot:
  • 1st row for Parent Industry = NA, because we set the default value to NA in sfdcDigest.
  • 1st and 2nd row for Account Source = null, because we set the default value to null in sfdcDigest.
  • 1st row for Employees and 2nd row for Annual Revenue = 0, Einstein Analytics auto set 0 for Measure field with null value.
  • 3rd and 4th row for Parent Industry = Parent not available, this is because there is parent lookup value, we use computeExpression to set the value, this is different with 1st row, where the parent lookup value is available, but Industry for that parent record is null.


Last update: 23 Sep 2019


Reference:


Friday, April 26, 2019

Salesforce: Account Hierarchy columns & Recently Viewed columns

Can we customize the Account Hierarchy columns?

Classic - NO
This is the article and this is the idea.

Lightning - YES
Here is the article and here the steps:
  • From Setup, at the top of the page, select Object Manager.
  • In Account, click Hierarchy Columns and then click New button if never created, or Edit link to edit the columns.
  • You can include up to 15 columns.


When you create Hierarchy Columns, system will auto create a new list view called "Org_Account_Hierarchy" and added to the Accounts list view menu, you can rename it, but not to change the sharing setting, deleting this item resets the columns to the defaults.

By default -- no hierarchy column setup, account hierarchies display the same columns as the Recently Viewed Accounts standard list view. However, the list view columns don’t change when you customize the hierarchy columns.


Recently Viewed List
In Classic, when we click a tab, such as Accounts tab, by default it will show "Recent Accounts" with columns defined in Search Layouts - Tab



While switching to Lightning, click Accounts tab will bring open the "Recently Viewed" list view (if pinned list view has not changed), list view columns in "Recently Viewed" is defined in Search Layouts - Search Result. This view isn’t deletable, change the visibility, or rename.

However, you will found another list view with a similar name but include object name in Lightning, e.g. Recently Viewed Accounts, however, we cannot configure the columns for this view (until Summer '19 release), and unable to delete, change the visibility, or rename it. So the easier is just to ignore it.




Reference:


Wednesday, April 24, 2019

Einstein Analytics: SAQL in computeExpression with samples

computeExpression is one of the most powerful features in Dataflow in computeExpression, you can "add" fields without having to change the source data.



1. Get field value - TEXT
'CreatedBy.Role.Name'
 as the field name contains a dot, always use ' before and after the field name

2. Set a text value - TEXT
"RoleName"
 always use " before and after the value for text

3. Get current date - DATE
now()

4. Get the first 18 characters - TEXT
substr('RECORD_ID', 1, 18)
 use substr() function

5. Get the first 18 characters with len() - TEXT
substr(UltimateParentPath, len(UltimateParentPath)-17,18)
use len() function

6. Concatenate text - TEXT
'CreatedDate_Year' + "-" + 'CreatedDate_Month' + "-" + 'CreatedDate_Day'
  use + to concatenate string

7. Concatenate text in case - TEXT
case when isDuplicate is null then 'Name' else 'Name' + " (" +'Username'+ ")" end
 use case function

8. Using multiple when in Case and compare Text - TEXT
case when 'Opportunity.Sales_Type__c' == "A" then "Type A" 
     when 'Opportunity.Sales_Type__c' == "B" then "Type B"  
     else "Type C" 
end
 use == to compare equal and use != to compare not equal

9. Check is Null - TEXT
case when 'Opportunity.Name' is null then "Yes" else "No" end
use is null keyword

10. Check is Not Null - TEXT
case when 'OptySplit.SplitOwnerId' is not null then 'OptySplit.SplitOwnerId' else 'OwnerId' end
use is not null keyword

11. Use && and ! as alternative - TEXT
case when 'Owner.Name' is null && !('Queue.Name' is null) then "Queue" 
     when !('Owner.Name' is null) then "User" 
     else "N/A" 
end
 use || as OR; use && as AND

12. Use && and ! as alternative to get field value - TEXT
case when 'Owner.Name' is null && !('Queue.Name' is null) then 'Queue.Name' 
     when !('Owner.Name' is null) then 'Owner.Name' 
     else "N/A" 
end

13. Simple bucketing - TEXT
case 
  when Value == 0 then "[1] 0"
  when Value <= 1000000 then "[2] 0-1M"
  when Value <= 25000000 then "[3] 1M-25M"
  when Value <= 100000000 then "[4] 25M-100M"
  else "[5] 100+M"
end

14. Get numeric value from field - NUMERIC
case 
  when Type_Data is not null and Type__c = "Type A" then Annual_Data
  when Type_Value is not null and Type__c = "Type B" then Annual_Value
end
else keyword is not a must in case, ' is not a must if the field does not contain dot

15. Check Neglected Case - TEXT
case when DaysSinceLastActivity >= 60 then "true" else "false" end

16. Check Is Lost - TEXT
case when 'IsClosed' == "true" && 'IsWon' == "false" then "Yes" else "No" end
there is NO BOOLEAN type in Einstein Analytics, so always enclosed wth "

17. Using IN - TEXT
case when 'Opportunity.StageName' in ["Stage 1", "Stage 2", "Stage 3", "Stage 4"] then "true" else "false" end
 use in[] function

18. Check is Overdue - TEXT
case when ('IsClosed' == "false") && (daysBetween(toDate(substr('ActivityDate', 1, 10), "yyyy-MM-dd"), now()) > 0) then "true" else "false" end
use daysBetween() function

19. Get Days Overdue - NUMERIC
case when 'IsOverdue' == "true" then daysBetween(toDate(substr('ActivityDate', 1, 10), "yyyy-MM-dd"), now()) else 0 end

20. Check is between 2-30 days - TEXT
(case when date('TIMESTAMP_DERIVED_Year', 'TIMESTAMP_DERIVED_Month', 'TIMESTAMP_DERIVED_Day') in ["30 days ago".."2 days ago"] then "yes" else "no" end)
use date() funtion

21. Check is Yesterday - TEXT
(case when date('TIMESTAMP_DERIVED_Year', 'TIMESTAMP_DERIVED_Month', 'TIMESTAMP_DERIVED_Day') in ["1 day ago".."current day"] then "yes" else "no" end)

22. Check is Past Due - TEXT
case when IsClosed == "false" && (toDate(CloseDate_sec_epoch) < now()) then "true" else "false" end
use toDate() and _sec_epoch field

23. Duration in Second - NUMERIC
date_diff("second", toDate(ValidFromDate_sec_epoch), now())
use date_diff() function

24. Check Is Closed - TEXT
case when daysBetween(toDate(ActivityDate_sec_epoch), now()) >= 0 then "true" else "false" end

25. Get days since last activity - NUMERIC
case    
   when LastActivityDate is null then daysBetween(toDate(LastModifiedDate_sec_epoch), now())   
   when LastModifiedDate > LastActivityDate then daysBetween(toDate(LastModifiedDate_sec_epoch), now())   
   else daysBetween(toDate(LastActivityDate_sec_epoch), now()) 
end

26. Get Past Due Date - NUMERIC
case when IsClosed == "false" && (toDate(CloseDate_sec_epoch) < now()) then daysBetween(toDate(CloseDate_sec_epoch), now()) else 0 end

27. Get Opportunity Age - NUMERIC
case when IsClosed == "false" then daysBetween(toDate(CreatedDate_sec_epoch), now()) else daysBetween(toDate(CreatedDate_sec_epoch),toDate(CloseDate_sec_epoch)) end

28. Get Lead Age - NUMERIC
case when ('IsConverted' == "false") then daysBetween(toDate(CreatedDate_sec_epoch), now()) else daysBetween(toDate(ConvertedDate_day_epoch), toDate(CreatedDate_day_epoch)) end

29. Get Case Duration - NUMERIC
case when ('IsClosed' == "true") then ('ClosedDate_sec_epoch' - 'CreatedDate_sec_epoch')/86400 else ('CurrentDate_sec_epoch' - 'CreatedDate_sec_epoch')/86400 end

30. Get Opportunity Age - NUMERIC
case 
when IsClosed == "true" && CloseDate_day_epoch - CreatedDate_day_epoch > 0 then CloseDate_day_epoch - CreatedDate_day_epoch
when IsClosed == "true" && CloseDate_day_epoch - CreatedDate_day_epoch <= 0 then 0
else round((date_to_epoch(now()) - CreatedDate_sec_epoch) /86400,0)
end

in the above sample, we check:
1). if the opportunity is Closed and Closed Date is after Created Date, then Age = Closed Date - Created Date
2). if the opportunity is Closed and Closed Date is before or equal Created Date, then age = 0
3). if the opportunity is Open, then age = now() - Created Date

Another option to calculate the age for (1) is to use date_diff() function:
date_diff("day", toDate(CreatedDate_sec_epoch), toDate(CloseDate_sec_epoch))

Please note that limitation of the maximum amount of time returned from date_diff() is 9,223,372,036,854,775,807 nanoseconds or 106,751.99 days.


31. Converting Created Date to PST - DATE
toDate('CreatedDate_sec_epoch'-3600*8)

32. Using starts_with(), ends_with, and lower() to compare string - TEXT
case
  when starts_with(lower(Subject),"call") then "Call"
  when ends_with(lower(Subject),"call") then "Call"
  else "Others"
end
 the one contain full string must be at left, it is case sensitive, so use lower() to help

33. Use matches() for contain - TEXT
case when "abcd" matches "abc" then "found" else "not found" end
 the full sentence must be at left, this operator is not case-sensitive, requires at least two characters

case when 'Product_Name' matches "cable" then "found" else "not found" end 
 this will work

case when "cable" matches 'Product_Name' then "found" else "not found" end 
 this is not allowed with error Invalid function argument: 'Product_Name', the second operand must be text.

case when !('Product_Name' matches "cable") then "a" else "b" end 
 use ! as not

  

Reference:

Einstein Analytics: using Allow disjoint schema to transform dataset

Here is the use case, we have multiple columns for each type to store value, this cause we can't really easily build a chart when the values are spread across many columns.

Solution: to transform the data source by splitting into many rows and using 1 column.



Dataflow



Inside computeExpression computeTYPE1 nodes:

Inside Type_TYPE1 Computed Field:
this is text, which is the field name

Inside Value_TYPE1 Computed Field:
this is numeric, which is the field value


Do the same for computeExpression Type 2 and Type 3. Then, combine all the data using append node


Once we have all the values spread across rows, use sliceDataset transformation to drop the original Type 1, Type 2, Type 3 fields.



Reference




Monday, April 8, 2019

Salesforce: User current app

Question: is there a way to check what is the user current app?

Answer: yes, but only for Lightning.


UserAppInfo
Since API version 38.0, Salesforce introduces an object called UserAppInfo, this object stores the last Lightning app users logged in to.

Sample query: SELECT Id, UserId, AppDefinitionId, FormFactor, CreatedById, CreatedDate, LastModifiedById, LastModifiedDate FROM UserAppInfo WHERE UserId = '00580000004JEfS'


Notes:
- AppDefinitionId: the ID of the last Lightning app that the user logged in to.
- FormFactor: The relative size of the app as displayed, values are:
     Small—suitable for a small device like a mobile phone
     Medium—suitable for a tablet
     Large—suitable for a large display device, like a monitor

Since AppDefinitionId is updateable, this means we can mass update the users' app.


AppDefinition
This object represents the metadata of an app and its navigation items. This object is available in API version 43.0 and later.

Sample query: SELECT DurableId, Label, UiType, Description, DeveloperName, MasterLabel, NavType, UtilityBar FROM AppDefinition ORDER BY Label



Notes:
- DurableId: instead of Id, DurableId represent App Id as in use for UserAppInfo
- UiType: option: Aloha for Classic, and Lightning
- NavType: option: Standard and Console
- UtilityBar: only available for Lightning


Reference:


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