2012-11-13 25 views
11

Reality Beschreibung: Wir haben eine Liste von Projekten. In jedem Projekt gibt es viele Konten. Sie können viele Aktionen für jedes Konto ausführen. Ich habe folgende Dimensionen und Faktentabelle definiert (vereinfacht):OLAP - Berechnen Sie Run-Off-Dreiecke, Beispieldaten und Würfel enthalten (PostgreSQL/Mondrian)

Dimensions and attributes: 
Project 
    project_key 
    project_name 
    industry 
    number_of_accounts 
Distance 
    distance_key 
    distance_in_months 
    distance_in_quarters 
Account 
    account_key 
    project_key 
    account_id 
Fact Table and attributes: 
Action_Fact_Table 
    project_key 
    distance_key 
    account_key 
    action_id 

Nun würde Ich mag Run-off-Dreieck Ansatz verwenden, um Daten zu analysieren (es ist vielleicht nicht das eigentliche Abwicklungsdreieck, aber der Ansatz ist dasselbe). Das einfachste Dreieck würde folgendermaßen aussehen:

Es läuft die Summe der Anzahl der Aktionen nach Zeilen. Distanz in Monaten zeigt die Entfernung zwischen Datum der Aktion und Projektstartdatum. Sie können natürlich ein ähnliches Dreieck erstellen, indem Sie die Entfernung in Vierteln (oder jeder anderen in der Abstandsdimension definierten Periode) verwenden.

Sie können auch Triangel für verschiedene Hierarchieebenen in der Projektdimension erstellen, z. Industrie (Project1-Project3 = Branche1, Projekt4-Project5 = Branche2):

   Distance in Months 
Project name|  1 2 3 4 5 6 7 8 9 10 
------------------------------------------------------------------------- 
Industry1 | 14 29 44 59 74 92 109 126 108 50 
Industry2 |  5 14 23 30 39 53 40 

Es gibt auch fortgeschrittenere Abwicklungsdreieck, wo Sie Summe der Maßnahmen durch die Anzahl der Konten unterteilen ausgeführt wird. Angenommen, es ist die folgende Anzahl von Konten für unsere Projekte:

Project_name number_of_accounts 
----------------------------- 
Project1  100 
Project2  100 
Project3  100 
Project4  100 
Project5  200 

Dann würde Ich mag das folgende Dreieck erhalten:

   Distance in Months 
Project |  1 2 3 4 5 6 7 8 9 10 
------------------------------------------------------------------------ 
Project1 | .05 .01 .15 .20 .25 .30 .35 .40 .45 .50 
Project2 | .7 .14 .21 .28 .35 .42 .49 .56 .63 
Project3 | .2 .5 .8 .11 .14 .20 .25 .30 
Project4 | .0 .2 .5 .10 .18 .23 .40 
Project5 | .05 .06 .09 .10 .105 .15 

Dies ist besonders nützlich, wenn Sie Projekte vergleichen möchten und ihre Aktionen wenn die Anzahl der Konten im Projekt nicht für alle Projekte gleich ist.

Die Frage ist, ob es möglich ist, eine solche Berechnung in OLAP zu erstellen. Ich dachte, ich könnte number_of_accounts in der Projekttabelle verwenden, aber ich kann es nicht herausfinden. Die andere Option besteht darin, Daten in der Kontodimension zu aggregieren. Ich konnte auch nichts mit Google finden, vielleicht weil ich eine falsche Frage stelle.

Die Lösung dieser Frage ist in vielen Branchen weit verbreitet, vor allem im Versicherungs- und Bankwesen. Es kann überall dort eingesetzt werden, wo Prozesse ein langes Leistungsfenster haben und durch genau definierte, vergleichbare Chargen von Einheiten verfolgt werden können.

(Wir verwenden PostgreSQL, Saiku, Würfel in Schema Workbench definiert sind)

Testdaten (PostgreSQL Syntax, lassen Sie mich wissen, wenn Sie etwas anderes benötigen)

--drop table if exists project cascade; 
create table project (
    project_key int primary key, 
    project_name character varying, 
    industry character varying, 
    number_of_accounts int 
); 

--drop table if exists distance cascade; 
create table distance (
    distance_key int primary key, 
    distance_in_months int, 
    distance_in_quarters int); 

--drop table if exists account cascade; 
create table account (
    account_key int primary key, 
    project_key int references project (project_key) 
); 

--drop table if exists action_fact_table cascade; 
create table action_fact_table (
    project_key int references project (project_key), 
    distance_key int references distance (distance_key), 
    account_key int references account (account_key), 
    action_id int 
); 

-- project data 
insert into project values (1,'Project1','Industry1',100); 
insert into project values (2,'Project2','Industry1',100); 
insert into project values (3,'Project3','Industry1',100); 
insert into project values (4,'Project4','Industry2',100); 
insert into project values (5,'Project5','Industry2',200); 

-- distance data 
insert into distance values(1,1,1); 
insert into distance values(2,2,1); 
insert into distance values(3,3,1); 
insert into distance values(4,4,2); 
insert into distance values(5,5,2); 
insert into distance values(6,6,2); 
insert into distance values(7,7,3); 
insert into distance values(8,8,3); 
insert into distance values(9,9,3); 
insert into distance values(10,10,4); 
insert into distance values(11,11,4); 
insert into distance values(12,12,4); 

-- account data 
/* let me know if you need insert statement for every row */ 
insert into account (
select generate_series (1,100), 1 union all 
select generate_series (101,200), 2 union all 
select generate_series (201,300), 3 union all 
select generate_series (301,400), 4 union all 
select generate_series (401,600), 5 
); 

insert into action_fact_table values(1,1,90,10001); 
insert into action_fact_table values(1,1,32,10002); 
insert into action_fact_table values(1,1,41,10003); 
insert into action_fact_table values(1,1,54,10004); 
insert into action_fact_table values(1,1,45,10005); 
insert into action_fact_table values(1,2,22,10006); 
insert into action_fact_table values(1,2,29,10007); 
insert into action_fact_table values(1,2,41,10008); 
insert into action_fact_table values(1,2,89,10009); 
insert into action_fact_table values(1,2,15,10010); 
insert into action_fact_table values(1,3,32,10011); 
insert into action_fact_table values(1,3,100,10012); 
insert into action_fact_table values(1,3,72,10013); 
insert into action_fact_table values(1,3,80,10014); 
insert into action_fact_table values(1,3,10,10015); 
insert into action_fact_table values(1,4,12,10016); 
insert into action_fact_table values(1,4,45,10017); 
insert into action_fact_table values(1,4,83,10018); 
insert into action_fact_table values(1,4,42,10019); 
insert into action_fact_table values(1,4,33,10020); 
insert into action_fact_table values(1,5,22,10021); 
insert into action_fact_table values(1,5,27,10022); 
insert into action_fact_table values(1,5,59,10023); 
insert into action_fact_table values(1,5,32,10024); 
insert into action_fact_table values(1,5,70,10025); 
insert into action_fact_table values(1,6,32,10026); 
insert into action_fact_table values(1,6,5,10027); 
insert into action_fact_table values(1,6,15,10028); 
insert into action_fact_table values(1,6,70,10029); 
insert into action_fact_table values(1,6,43,10030); 
insert into action_fact_table values(1,7,59,10031); 
insert into action_fact_table values(1,7,9,10032); 
insert into action_fact_table values(1,7,99,10033); 
insert into action_fact_table values(1,7,79,10034); 
insert into action_fact_table values(1,7,31,10035); 
insert into action_fact_table values(1,8,56,10036); 
insert into action_fact_table values(1,8,34,10037); 
insert into action_fact_table values(1,8,48,10038); 
insert into action_fact_table values(1,8,79,10039); 
insert into action_fact_table values(1,8,42,10040); 
insert into action_fact_table values(1,9,10,10041); 
insert into action_fact_table values(1,9,10,10042); 
insert into action_fact_table values(1,9,49,10043); 
insert into action_fact_table values(1,9,61,10044); 
insert into action_fact_table values(1,9,49,10045); 
insert into action_fact_table values(1,10,99,10046); 
insert into action_fact_table values(1,10,69,10047); 
insert into action_fact_table values(1,10,84,10048); 
insert into action_fact_table values(1,10,99,10049); 
insert into action_fact_table values(1,10,3,10050); 
insert into action_fact_table values(2,1,182,10051); 
insert into action_fact_table values(2,1,127,10052); 
insert into action_fact_table values(2,1,197,10053); 
insert into action_fact_table values(2,1,174,10054); 
insert into action_fact_table values(2,1,187,10055); 
insert into action_fact_table values(2,1,144,10056); 
insert into action_fact_table values(2,1,160,10057); 
insert into action_fact_table values(2,2,155,10058); 
insert into action_fact_table values(2,2,153,10059); 
insert into action_fact_table values(2,2,119,10060); 
insert into action_fact_table values(2,2,188,10061); 
insert into action_fact_table values(2,2,125,10062); 
insert into action_fact_table values(2,2,147,10063); 
insert into action_fact_table values(2,2,123,10064); 
insert into action_fact_table values(2,3,136,10065); 
insert into action_fact_table values(2,3,163,10066); 
insert into action_fact_table values(2,3,187,10067); 
insert into action_fact_table values(2,3,138,10068); 
insert into action_fact_table values(2,3,168,10069); 
insert into action_fact_table values(2,3,132,10070); 
insert into action_fact_table values(2,3,138,10071); 
insert into action_fact_table values(2,4,158,10072); 
insert into action_fact_table values(2,4,171,10073); 
insert into action_fact_table values(2,4,153,10074); 
insert into action_fact_table values(2,4,141,10075); 
insert into action_fact_table values(2,4,182,10076); 
insert into action_fact_table values(2,4,165,10077); 
insert into action_fact_table values(2,4,143,10078); 
insert into action_fact_table values(2,5,190,10079); 
insert into action_fact_table values(2,5,181,10080); 
insert into action_fact_table values(2,5,163,10081); 
insert into action_fact_table values(2,5,134,10082); 
insert into action_fact_table values(2,5,145,10083); 
insert into action_fact_table values(2,5,190,10084); 
insert into action_fact_table values(2,5,198,10085); 
insert into action_fact_table values(2,6,137,10086); 
insert into action_fact_table values(2,6,133,10087); 
insert into action_fact_table values(2,6,135,10088); 
insert into action_fact_table values(2,6,103,10089); 
insert into action_fact_table values(2,6,187,10090); 
insert into action_fact_table values(2,6,127,10091); 
insert into action_fact_table values(2,6,117,10092); 
insert into action_fact_table values(2,7,116,10093); 
insert into action_fact_table values(2,7,139,10094); 
insert into action_fact_table values(2,7,111,10095); 
insert into action_fact_table values(2,7,150,10096); 
insert into action_fact_table values(2,7,151,10097); 
insert into action_fact_table values(2,7,181,10098); 
insert into action_fact_table values(2,7,109,10099); 
insert into action_fact_table values(2,8,102,10100); 
insert into action_fact_table values(2,8,101,10101); 
insert into action_fact_table values(2,8,118,10102); 
insert into action_fact_table values(2,8,147,10103); 
insert into action_fact_table values(2,8,186,10104); 
insert into action_fact_table values(2,8,136,10105); 
insert into action_fact_table values(2,8,160,10106); 
insert into action_fact_table values(2,9,149,10107); 
insert into action_fact_table values(2,9,119,10108); 
insert into action_fact_table values(2,9,169,10109); 
insert into action_fact_table values(2,9,176,10110); 
insert into action_fact_table values(2,9,195,10111); 
insert into action_fact_table values(2,9,183,10112); 
insert into action_fact_table values(2,9,140,10113); 
insert into action_fact_table values(3,1,224,10114); 
insert into action_fact_table values(3,1,241,10115); 
insert into action_fact_table values(3,2,295,10116); 
insert into action_fact_table values(3,2,249,10117); 
insert into action_fact_table values(3,2,260,10118); 
insert into action_fact_table values(3,3,298,10119); 
insert into action_fact_table values(3,3,267,10120); 
insert into action_fact_table values(3,3,297,10121); 
insert into action_fact_table values(3,4,211,10122); 
insert into action_fact_table values(3,4,253,10123); 
insert into action_fact_table values(3,4,214,10124); 
insert into action_fact_table values(3,5,248,10125); 
insert into action_fact_table values(3,5,223,10126); 
insert into action_fact_table values(3,5,288,10127); 
insert into action_fact_table values(3,6,207,10128); 
insert into action_fact_table values(3,6,296,10129); 
insert into action_fact_table values(3,6,221,10130); 
insert into action_fact_table values(3,6,201,10131); 
insert into action_fact_table values(3,6,227,10132); 
insert into action_fact_table values(3,6,209,10133); 
insert into action_fact_table values(3,7,267,10134); 
insert into action_fact_table values(3,7,282,10135); 
insert into action_fact_table values(3,7,215,10136); 
insert into action_fact_table values(3,7,285,10137); 
insert into action_fact_table values(3,7,212,10138); 
insert into action_fact_table values(3,8,239,10139); 
insert into action_fact_table values(3,8,294,10140); 
insert into action_fact_table values(3,8,296,10141); 
insert into action_fact_table values(3,8,251,10142); 
insert into action_fact_table values(3,8,281,10143); 
insert into action_fact_table values(4,2,392,10144); 
insert into action_fact_table values(4,2,347,10145); 
insert into action_fact_table values(4,3,318,10146); 
insert into action_fact_table values(4,3,400,10147); 
insert into action_fact_table values(4,3,378,10148); 
insert into action_fact_table values(4,4,315,10149); 
insert into action_fact_table values(4,4,318,10150); 
insert into action_fact_table values(4,4,394,10151); 
insert into action_fact_table values(4,4,382,10152); 
insert into action_fact_table values(4,4,317,10153); 
insert into action_fact_table values(4,5,314,10154); 
insert into action_fact_table values(4,5,354,10155); 
insert into action_fact_table values(4,5,338,10156); 
insert into action_fact_table values(4,5,375,10157); 
insert into action_fact_table values(4,5,317,10158); 
insert into action_fact_table values(4,5,329,10159); 
insert into action_fact_table values(4,5,342,10160); 
insert into action_fact_table values(4,5,380,10161); 
insert into action_fact_table values(4,6,313,10162); 
insert into action_fact_table values(4,6,311,10163); 
insert into action_fact_table values(4,6,336,10164); 
insert into action_fact_table values(4,6,380,10165); 
insert into action_fact_table values(4,6,355,10166); 
insert into action_fact_table values(4,7,386,10167); 
insert into action_fact_table values(4,7,322,10168); 
insert into action_fact_table values(4,7,311,10169); 
insert into action_fact_table values(4,7,367,10170); 
insert into action_fact_table values(4,7,350,10171); 
insert into action_fact_table values(4,7,384,10172); 
insert into action_fact_table values(4,7,391,10173); 
insert into action_fact_table values(4,7,331,10174); 
insert into action_fact_table values(4,7,373,10175); 
insert into action_fact_table values(4,7,314,10176); 
insert into action_fact_table values(4,7,305,10177); 
insert into action_fact_table values(4,7,331,10178); 
insert into action_fact_table values(4,7,350,10179); 
insert into action_fact_table values(4,7,376,10180); 
insert into action_fact_table values(4,7,387,10181); 
insert into action_fact_table values(4,7,312,10182); 
insert into action_fact_table values(4,7,397,10183); 
insert into action_fact_table values(5,1,404,10184); 
insert into action_fact_table values(5,1,562,10185); 
insert into action_fact_table values(5,1,511,10186); 
insert into action_fact_table values(5,1,594,10187); 
insert into action_fact_table values(5,1,541,10188); 
insert into action_fact_table values(5,2,506,10189); 
insert into action_fact_table values(5,2,427,10190); 
insert into action_fact_table values(5,2,481,10191); 
insert into action_fact_table values(5,2,463,10192); 
insert into action_fact_table values(5,2,579,10193); 
insert into action_fact_table values(5,2,455,10194); 
insert into action_fact_table values(5,2,527,10195); 
insert into action_fact_table values(5,3,465,10196); 
insert into action_fact_table values(5,3,562,10197); 
insert into action_fact_table values(5,3,434,10198); 
insert into action_fact_table values(5,3,401,10199); 
insert into action_fact_table values(5,3,464,10200); 
insert into action_fact_table values(5,3,500,10201); 
insert into action_fact_table values(5,4,554,10202); 
insert into action_fact_table values(5,4,600,10203); 
insert into action_fact_table values(5,5,483,10204); 
insert into action_fact_table values(5,6,552,10205); 
insert into action_fact_table values(5,6,565,10206); 
insert into action_fact_table values(5,6,586,10207); 
insert into action_fact_table values(5,6,544,10208); 
insert into action_fact_table values(5,6,436,10209); 
insert into action_fact_table values(5,6,531,10210); 
insert into action_fact_table values(5,6,409,10211); 
insert into action_fact_table values(5,6,524,10212); 
insert into action_fact_table values(5,6,564,10213); 

Musterwürfel (Mondrian) :

<Schema name="RunoffTriangleSchema"> 
    <Cube name="RunoffTriangleCube" visible="true" cache="true" enabled="true"> 
    <Table name="action_fact_table" schema="public"> 
    </Table> 
    <Dimension type="StandardDimension" visible="true" foreignKey="project_key" name="Project"> 
     <Hierarchy name="Project" visible="true" hasAll="true"> 
     <Table name="project" schema="public" alias=""> 
     </Table> 
     <Level name="Industry" visible="true" column="industry" uniqueMembers="false"> 
     </Level> 
     <Level name="Project Name" visible="true" column="project_name" uniqueMembers="false"> 
     </Level> 
     </Hierarchy> 
    </Dimension> 
    <Dimension type="StandardDimension" visible="true" foreignKey="distance_key" name="Distance"> 
     <Hierarchy name="Distance" visible="true" hasAll="true"> 
     <Table name="distance" schema="public" alias=""> 
     </Table> 
     <Level name="Distance In Quarters" visible="true" column="distance_in_quarters" uniqueMembers="false"> 
     </Level> 
     <Level name="Distance In Months" visible="true" column="distance_in_months" uniqueMembers="false"> 
     </Level> 
     </Hierarchy> 
    </Dimension> 
    <Dimension type="StandardDimension" visible="true" foreignKey="account_key" name="Account"> 
     <Hierarchy name="Account" visible="true" hasAll="true"> 
     <Table name="account" schema="public"> 
     </Table> 
     <Level name="Account Key" visible="true" column="account_key" uniqueMembers="false"> 
     </Level> 
     </Hierarchy> 
    </Dimension> 
    <Measure name="CountActions" column="action_id" aggregator="count" visible="true"> 
    </Measure> 
    </Cube> 
</Schema> 

Antwort

2

Zwei Kopfgelder und keine Antwort, ich bin überrascht. Ich habe eine Workaround-Lösung gefunden - mit SQL und BIRT-Engine bin ich jetzt nah dran an dem, wonach ich gesucht habe. Ich hoffe immer noch, dass jemand das für OLAP lösen kann.


Um diese Arbeit zu machen, die ich habe: 2,6

  • Benutzerdefinierte Funktion
  • SQL dynamisch ausgewählten Spalten zurück auf ausgewählte Spalten Abwicklungsdreieck Daten zu berechnen basierend
  • Bericht in BIRT .1 zum Anzeigen der Ergebnisse und zum Bereitstellen der Schnittstelle für die Parameterauswahl

Dynamisch Rück Spalten

CREATE or replace FUNCTION bizdata.getColumns(_column1 text, _column2 text, _column3 text, _column4 text, _table text, _rqdl text) 
     RETURNS TABLE(cmf1 text, cmf2 text, cmf3 text, outval numeric, rqdl text) AS $$ 
    BEGIN 
     RETURN QUERY EXECUTE 
      'SELECT ' 
       || case when _column1 = 'None' then quote_literal('None') else quote_ident(_column1) end || '::text as cmf1,' 
       || case when _column2 = 'None' then quote_literal('None') else quote_ident(_column2) end || '::text as cmf2,' 
       || case when _column3 = 'None' then quote_literal('None') else quote_ident(_column3) end || '::text as cmf3,' 
       || quote_ident(_column4) || '::numeric as baseline,' 
       || case when _rqdl = 'None' then 0::text else quote_ident(_rqdl)::text end || '::text as rqdl' 
      ' FROM ' 
       || 'bizdata.' || _table; 
    END; 
    $$ LANGUAGE plpgsql; 

Thi function takes the following as input variables: 

- _column1 - common mapping field number 1 
- _column2 - common mapping field number 2 
- _column3 - common mapping field number 3 
- _column4 - column used for aggregation (sum) 
- _table - table used for getting data 
- _rqdl - requested distance level 

berechnen Daten

Using bizdata.getColumns() function I can calculate triangle data using the following statement: 


with 

params as (
    select 'cmf1'::varchar as prm_name, 'project_owner_name_short'::varchar as prm_value union all 
    select 'cmf2'::varchar as prm_name, 'project_source_name_short'::varchar as prm_value union all 
    select 'cmf3'::varchar as prm_name, 'None'::varchar as prm_value union all 
    select 'fact'::varchar as prm_name, 'amount'::varchar as prm_value union all  
    select 'fact_table'::varchar as prm_name, 'dwv_daily_allocation_fact'::varchar as prm_value union all  
    select 'baseline'::varchar as prm_name, 'tmp_nominal_value'::varchar as prm_value union all 
    select 'baseline_table'::varchar as prm_name, 'dw_project'::varchar as prm_value union all 
    select 'rqdl'::varchar as prm_name, 'year_distance'::varchar as prm_value 
) 

,baseline_data as (
    select 
     cmf1, 
     cmf2, 
     cmf3, 
     sum(coalesce(outval,0)) as baseline 
    from 
     bizdata.getColumns(
      (select prm_value from params where prm_name = 'cmf1'::text), 
      (select prm_value from params where prm_name = 'cmf2'::text), 
      (select prm_value from params where prm_name = 'cmf3'::text), 
      (select prm_value from params where prm_name = 'baseline'::text), 
      (select prm_value from params where prm_name = 'baseline_table'::text), 
      'None' 
      ) 
    group by 
     cmf1, 
     cmf2, 
     cmf3 

) 




,fact_data as (
    select 
     cmf1, 
     cmf2, 
     cmf3, 
     rqdl::int as rqdl, 
     sum(coalesce(outval,0)) as fact 
    from 
     bizdata.getColumns(
      (select prm_value from params where prm_name = 'cmf1'::text), 
      (select prm_value from params where prm_name = 'cmf2'::text), 
      (select prm_value from params where prm_name = 'cmf3'::text), 
      (select prm_value from params where prm_name = 'fact'::text), 
      (select prm_value from params where prm_name = 'fact_table'::text), 
      (select prm_value from params where prm_name = 'rqdl'::text) 
      ) 
    group by 
     cmf1, 
     cmf2, 
     cmf3, 
     rqdl 

) 

select 
    case when cmf1 = 'None' then null else cmf1 end as cmf1, 
    case when cmf2 = 'None' then null else cmf1 end as cmf, 
    case when cmf3 = 'None' then null else cmf1 end as cmf1, 
    rqdl, 
    fact, 
    baseline, 
    sum(fact) over (partition by cmf1, cmf2, cmf3 order by rqdl) as cfact, 
    sum(fact) over (partition by cmf1, cmf2, cmf3 order by rqdl)/baseline as cfactpct 
from 
    fact_data 
    join baseline_data using (cmf1, cmf2, cmf3) 

Sie können sehen, dass ich Gruppenvariablen bis 3 verwenden kann (CMF1, CMF2, CMF3) und wählen Sie eine beliebige Distanz Attribut (so lange da das Attribut in dwv_daily_allocation_fact verfügbar ist. Gruppieren von Variablen sollten verfügbar sein, sowohl in Baseline-Tabelle und Faktentabelle (auf gemeinsame Konzernebene zu erhalten)

Bericht

Letzter Schritt ist Bericht in BIRT zu erstellen (2.6.1) wobei die Parameter in params Teil von SQL werden durch Datensatzparameter ersetzt und mit Berichtsparametern verknüpft. Diejenigen, die BIRT benutzen, werden es wahrscheinlich verstehen, andere müssen einen anderen Weg finden.

Parameter Auswahl GUI Parameters selection GUI

Ausgabe Bericht enter image description here

Ich habe immer noch korrekte Sortierung der Tabelle herausfinden (so Gruppen mit der längsten Geschichte sind erste

bearbeiten.: Ich habe herausgefunden, dass das Sortieren in BIRT-Kreuztabellen funktioniert, jetzt sieht es wie echtes Dreieck aus:

enter image description here

Lassen Sie mich wissen, wenn Sie eine detailliertere Beschreibung benötigen, wie ich das gemacht habe.

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Gut hören Sie Fortschritte machen . Ich vermute, dass das Fehlen von Antworten darauf zurückzuführen ist, dass Sie auf dem neuesten Stand eines etwas unbekannten Technologie-Stacks sind. –

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@MikeHoney Könnte obskure Technologie sein, aber die Frage ist generisch - lassen Sie uns wissen, wenn Sie Antwort für MS-Technologie oder andere wissen. –

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Ich würde wahrscheinlich die RunningValue-Funktion in SSRS (Reporting Services) verwenden –

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Ich habe R-Paket namens pgvint erstellt, wo Vintage-Kurven (Run-Off-Dreiecke) leicht berechnet werden können. Das Paket ist auf github und derzeit wird nur PostgreSQL als Datenquelle unterstützt.

Beispiel Ausgabe: enter image description here

enter image description here

Außerdem gibt es Shiny app, wo Vintage-Daten in verschiedenen Layouts können interaktiv angezeigt werden:

enter image description here