oracle bi sample app v1.2

Oracle Business In

tellig

ence Suite

Enterpris

e Editio

n (B

I EE) 1

0.1.3.4 O

BI E

E

Samples SalesContent G

uide (1

.2)

PART 1 of 2

Oracle Business Intelligence Product Management

September, 2

008

Contents

Introduction

1.Dashboards and Reports Samples

A.Dashboards Overview

........

..Slide 5

B.Reports Details

...Slide 14

01 Ranks and Toppers

02 History

03 Tiering

04 Distribution

05 Benchmarking

Other Reports

2.Repository Samples

A.Overview

...Slide 73

B.How to Demoselected RPD features

...Slide 81

C.Logical Aggregations details

...Slide 95

10.1.3.4 Sample Sales Content

Intro

ductio

n

A new sample Oracle BI application and data set called Sample Sales"

has been provided in 10.1.3.4 to better illu

strate functional capabilitie

s of

Oracle BI EE and numerous best practices.

Offers an extended description of sample materials and help for Oracle

BI features

Provides useful examples and templates for customers

designed to demonstrate as much as possible of OBI EE capabilitie

s

Sample Salesreplaces the former P

aintcontent, but P

aintis still

provided with the install to

support existing materials

The Sample Salesapplication provides:

Interactive Dashboard Samples

RPD Constructs Samples

Samples Sales Content O

verview

WebPresentatio

n: T

ypical re

ports

examples

Showcasing specific Answers features

Answers formula building,

Layouts

Presentation Variables,

Filtering,

Navigations...

Reposito

ry : E

xamples of M

etadata constru

cts

intended to help design mappings for typ

ical functional requirements, and to demonstrate best practices

Numerous logical aggregations

Time series and Rolling X Months

Variations, Time Span Variations and Compounded Variations

Multi P

hysical Sourcing

Dimensional Snowflaking

Canonical Time Construct (M

ulti L

TS Facts tables)

Data security, p

rojects, segmentation metadata, etc

1.A D

ashboards O

verview

Overview of 10.1.3.4 Samples

Dashboards Content

1 -Rankings & Toppers

1.1 -Multi D

imensional Top Ns

1.2 -Multi M

etrics Top Ns

1.3 -Proportional Top Ns

1.4 -Top Values History

1.5 -Toppers H

istory

1.6 -Rank Changes

2 -History

2.1 -History

2.2 -Comparative Trending

2.3 -Indexing

2.4 -Year Seasonality B

y Month

2.5 -Quarter Seasonality B

y Week

2.6 -Month Seasonality B

y Day

3

Tierin

g3.1 -Eighty T

wenty

3.2 -Tiering

3.3 -BoxplotWhisker

3.4 -Waterfall Single Dimension

3.5 -Waterfall Double Dimension

3.6 -DecilingComparative

4

Distrib

utio

n

4.1 -Statistical Distribution

4.2 -Comparative Distribution

4.3 -Variability A

nalysis

4.4 -Scatter

4.5 -Standard Deviation Comparative

5

Benchmarking

5.1 -Benchmarking

5.2 -Index to

Average

5.3 -Trended Benchmarking

5.4 -Trended Indexing to Average

Other (u

nder O

verview Dashboard)

-Overview Page

-Business Profilin

g (hidden)

-Customer Details (hidden)

-Order Details (hidden)

Sample Sales Dashboards List


Top Individ

uals for tw

o distinct dimensions

on a single metric. Includes bi-dimensional

toppers matrix.

Measures how Top N layers of individ

uals

contributes to total aggregation of population, for

two distinct metrics.

Historical information on Top and Bottom N

individ

uals, fre

quency of individ

uals qualifyin

g for

Tops& Bottoms groups

Analysis of performance variations for individ

uals

ranking on selected metric, fro

m current period to

previous, or current ye

ar to previous year.

Represents trended information of Top and

Bottom N aggregate values, displayed as total,

average and proportional va

lues.

Single dimension top individ

uals analysis against

two distinct metrics

02 History

Details yearly, q

uarterly, m

onthly a

nd weekly

details and averages for a given metric, over a

period of tim

e selected

Indexed comparison of dimension individ

uals

values over tim

e, as opposed to absolute value

compariso

n.

Seasonality o

f a metric month by m

onth over

multiple years. Shows pattern of monthly va

lues by

year, over selected history.

Shows comparative

history a

nd seasonality c

harts on

one metric for individ

uals of a dimension.

Daily s

easonality o

f a metric over multiple months.

Shows pattern of daily va

lues by m

onth, over

selected history

Seasonality o

f a metric week by w

eek over multiple

quarters. S

hows pattern of week values by quarter,

over se

lected history

03 Tierin

g

Measures how the upper tie

r of a specific

population set co

ntributes in descending order

of va

lues. '20% of population that is responsible

for 80% of the value'.

Organizes individ

uals in descending order and

tiers total of metric in clusters of equal va

lues.

'How many in

divid

uals in each third of my to

tal

revenue, fro

m top to bottom ?

Comparative

analysis of dimension individ

uals

for several metrics

, ordered in descending way

of va

lues of a specific metric. How are my to

p

revenue deciles contributing to profit

Simple comparative

graphical summary o

f a set of data.

For each value in a dimension, it s

hows measures of

central, average, dispersion and skewness.

Shows how an initial va

lue is increased and

decreased by a series of intermediate values,

leading to a final total va

lue.

Shows how initial va

lue is increased and

decreased by a series of intermediate values,

breaking down details o

f dimension individ

uals for

each intermediate value.

04 Distrib

utio

n

Simple statistic

al discre

te distribution of

selected population over one metric.

Ability to

dynamically s

elect the number of

buckets to use for distribution.

Comparative

representation over multiple years, of

simple sta

tistical distribution for a selected population.

'How do sales order size distribute every ye

ar ?'

Relative

average measures fo

r top, middle and

bottom percentiles of se

lected population.

Simple graphical summary o

f a set of data. Displays

both scattered detail of each individ

uals in the set of

data and shows m

easures of central median,

dispersion and skewness.

Comparative

standard deviation analysis on a metric for

a selected set of population, with a selected grain for

analysis.

05 Benchmarking

Relative

performance of

individ

uals in a

dimension,

benchmarked

against a

dynamically u

ser

selected individ

ual.

Benchmarked performance

of dimension individ

uals,

against Average

performance of all

individ

uals in the report.

Indexed historica

l performance of dimension

individ

uals, against

Average performance of all

individ

uals in the report.

Relative

historical

performance of

individ

uals in a

dimension,

benchmarked

against a

dynamically u

ser

selected

individ

ual.

Selected examples of le

veraging 10.1.3.4 Sample

Sales Answers Features

Multi N

avigation : click on

hyperlinked figures and select

which detail to

navigate to.

Repeat process and further

navigate deeper into details

Web Variables leveraging :

Change values in top pages pink

boxes, and see how reports

queries change accordingly

Page help content : c

lick on help

hyperlinks to see contextual

functional help on dashboard you

are looking at

Visit O

verview page, see

summary c

ontent you have

access to and navigate to pages

by clicking on Openlinks

From detailed reports

(navigation targets), le

verage

table dynamic sorting and

direct segment/lis

t creation

link.

Pivot table level

calculations to extend

aggregations levels on top of

answers columns calculations

Selected examples of le

veraging 10.1.3.4 Sample

Sales Answers Features

Profile dashboard drillin

g and

dynamic filte

ring fro

m

segmentation page.

Answers level Aggregations : visit

definition of answers based

metrics with SQL based

aggregations

formulas on top

of existing RPD

objects

Union clause based answers

report a

nd charts, that leverage

capability o

f bringing together

results of several distinct queries

Leverage of Filter Groups

structure to allow advanced

filtering in reports, as well as

leverage of presavedprompted

filters

Conditional Chart series

formatting based on value of

series, to allow better visual

rendering in charts.

Visit bottom page formatting

features with prebuilt

Page Footers

examples

1.B D

ashboards Details


Analysis on top and bottom rankers,

their re

lative position, their history, how

individuals migrate from one layer to

another etc...

1.1 -Multi D

imensional T

op Ns

This page provides insight on top performers fro

m two distinct dimensions, on a single measurement.

The filte

ring on the reports only s

hows those individuals that belong to the top N list for at least one of

the dimensions considered

1.1 -Multi D

imensional T

op Ns

Chart 1

and 2respectiv

ely s

how top individ

uals for each dimension. That is, top N for the

dimension plus other individ

uals that qualify fo

r top N on the other dimension. In the example,

Dimension 1 is p

roduct a

nd Dimension 2 is Market. The ranking ineach chart is e

xpressed at

the dimension level, th

at is, ranking aggregation is grouped by th

e dimension of the respective

chart.

Chart 3

shows a representation of detailed rankings (c

ross-ranks). T

he colored legend allows

to quickly s

pot which combination of va

lues fo

r the two dimensions has th

e highest va

lue for the

metric, as well as how spread in the matrix a

re the descending layers o

f rankings.

1 -Functio

nal V

alue

This report is

useful to identify w

hich individuals are the top performers o

n a given metric.It p

resents th

e individuals if to

ppers by

dimensions next to

each other, and then also presents th

e combined individuals in a matrix fo

rmat. The value of the heatmap-like matrix

format is to allow a quick grasp at which combinations of the two dimensions are the most performing ones, and if m

ost of the toppers are

geographically lo

cated in the same area on the matrix. T

his chart ca

n help spot even/un-even business performance across the

organization.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (Sum All)"

Dim

ensional A

ttributes :

"D4 Product"."P

01 Product"

"D2 Market"."M

01 Market

5 -Answers Calculatio

ns :

All th

e columns w

ith Header labeled as 'A

nswers

Calc' in the report in

dicate answer calculations and

aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "T

op_N_Limit", d

efaults to

: 5,

Used to dynamically s

et the maxim

um Rank lim

it for

individuals to

appear in reports p

opulation.

This va

riable must b

e defined in a page prompt on

the dashboard page where this report is

exposed. In

the sample, this p

rompt object is n

amed : "P

rt TopN".

Specific

Filte

rs

A specific Filter is used in this report to

cumulative

ly filte

r in individ

uals that are within the Top N lim

it for

any of the 3 metrics considered. This filte

r is

leveraging group filte

ring and AND/OR filte

r operators.

2 -Layout O

bjects:

The 'S

et T

op N Lim

it'top page dashboard prompt allows the user to

dynamically fix th

e lim

it of top individ

uals to be displayed in the report.

Note that this filte

r will a

pply to

each dimension in the reportset

alternative

ly. For instance, in the example, Top N products and all th

e

markets that they are in, plus Top N Markets a

nd all th

e products th

at

they have, are represented. Other Prompts o

n the dashboard page are

filtering down the report sc

ope to a choice of context b

y the user.

3 -Drills

and Navigatio

ns

This p

age has both Drillin

g and Navigations enabled.

-clicks on dimension values w

ill drill d

own the logical hierarchical paths

-clicks on metric values and/or se

lected chart series w

ill offer

navigational menu to jump to other re

ports (w

hile reducing the scope to

only th

e individ

uals clicked)

1.2 -Multi M

etric

s Top Ns

Combined views of top individuals in a dimension, per tw

o distinct metrics values. The filte

ring on

the reports only s

hows those individuals that belong to the top N list for at least one of the metrics

considered.

1.2 -Multi M

etric

s Top Ns

The 'S

elect G

rain' d

rop down allows users to

set the detail of dimension grain to run the

analysis on. In the example, we are looking at top Customers in

divid

uals.

Chart 1

and 2respectiv

ely s

how top individ

uals (top N and other individuals that qualify fo

r top N

on other charts) for each metric considered in the report. In

the example, ch

art 1 shows value for

metric 1, ch

art 2 shows value for metric 2. Note that the color coding is identical across all th

e

charts, w

hich allows to quickly id

entify h

ow a given individ

ual ranks fo

r each metric. The same

color will m

atch the same individ

ual across all th

ree charts. In

the example, it's ve

ry quickly vis

ible

that individ

uals ranking top in Value are not ranking top in unit price for instance

Chart 3

shows a plotted representation of rankings for both dimension, expressed as indexes. to

allow quick comparison between rankings of the population. The size of the bubble of this c

hart is

proportional to Metric 1 value. Index Value of 100 represents to

p rank, any va

lue below is

proportional to the rank of the individ

ual in the population

Chart 4

shows a representation of rankings expressed as indexes. to allow quick comparison

between rankings of the population. Index Value of 100 represents to

p rank, any va

lue below is

proportional to the rank of the individ

ual in the population.

1 -Functio

nal V

alue

This report is


hich individuals are the top performers o

n a given set of measurements, and how well performances

correlated between the selected metrics

. Eg, are top revenue performers also among the top rankers in

collections and customer

satisfaction ? Are the plants producing top volumes also ranked top in quality a

nd efficiency m

easurements ? This chart can helpspot un-

even business performance development for individuals that focuson a single aspect of performance, at cost fo

r other measures.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (Sum All)""F

1

"F2 Units"."2

-01 Billed Qty (S

um All)"

Dim

ensional A

ttributes :

"D1 Customer"."C

1 Cust N

ame"


ns :

All th

e columns w


nswers



aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "T

op_N_Limit", d

efaults to

: 5,


et the maxim

um Rank lim

it for

individuals to

appear in reports p

opulation.

This va

riable must b



exposed. In

the sample, this p

rompt object is n

amed : "P

rt TopN".

Specific

Filte

rs


cumulative

ly filte

r in individ


it for


r is



r operators.

2 -Layout O

bjects:

The 'S

et T

op N Lim

it'top page dashboard prompt allows users to

dynamically fix th

e lim

it of top candidates elected to display in

the report.

This filte

r will a

pply to

each metric in

the report set, so, forthe example, a

limit se

t to 'top 5' may allow 10 distin

ct individ

uals to appearin the report

incase each top 5 for the 2 metrics in

the report are fully d

ifferent individ

uals.

3 -Drills

and Navigatio

ns

This p




ill drill d




ill offer


ports (w


only th

e individ

uals clicked)

1.3 -Proportio

nal T

op Ns

This page provides views of top individuals in a dimension alongwith an aggregation of all th

e non

Top N individuals, per distinct metrics values selected in the report. T

he filte

ring on the reports only

shows those individuals that belong to the top N list for at least one of the metrics considered

1.3 -Proportio

nal T

op Ns

Chart 1

and 2respectiv

ely s

how top individ

uals (top N and other individuals that qualify fo

r top N

on other charts) for each of the two metrics co

nsidered in the report. C

hart 1 shows value for

metric 1, and chart 2 shows value for metric 2

.

Note :Unlike Multi M

etrics Top Ns page, the color coding is N

OT identical across all th

e charts.

Same individ

ual may have different bar co

lor co

de in different charts fo

r this re

port.

Chart 3

and 4 show top individ

uals plotted as in

dex vs

average of the group for each of the two

metrics considered in the report. C

hart 3 plots th

ese in a bubble chart (s

ize of the bubble

proportional to Metric 1 values), ch

art 4 shows linear plotting of both metrics indexes.

Pivot T

able at th

e very botto

mshows allows a quick comparison of how each individ

ual ranks

in each metrics..

1 -Functio

nal V

alue

This report is


ho are the top performers on a given measurement, and to aggregate their im

portance relative to the total

population. This helps users understand the impact of top performers in the context o

f the whole business and may help balance business

decisions and actions on the top individuals.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

"F2 Units"."2

-01 Billed Qty (S

um All)

Dim

ensional A

ttributes :

"D5 Employee"."E

01 Employee Name"


ns :

All th

e columns w


nswers



aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "T

op_N_Limit", d

efaults to

: 10,


et the maxim

um Rank lim

it for

individuals to

appear in reports p

opulation.

This va

riable must b



exposed. In

the sample, this p

rompt object is n

amed : "P

rt TopN".

Specific

Filte

rs


cumulative

ly filte

r in individ


it for


r is



r operators.

2 -Layout O

bjects:

The 'S

et T

op N Lim

it'top page dashboard prompt allows the user to

dynamically s

et the lim

it of top N candidates to

be displayed inthe report.

Note that this filte

r will a

pply to

each metric in

the report set. In

other words,

a lim

it set to 'top 5' may display 15 matches in

each chart if e

ach of the top 5

individual for each metric is

distinct fro

m every o

ne else in the report. O

ther

Prompts on the dashboard page are filte

ring down the report sc

ope to a

choice of context b

y the user.

3 -Drills

and Navigatio

nsThis page has no Drillin

g nor Navigations enabled.


Historical amplitude of Top N and Bottom N value layers and visual indication of how values for Toppers and

Bottomers evolve over tim

e comparatively. F

or each month the report in

dicates how much of the total va

lue

was represented by Top and Bottom Ns.


Chart 1

displays a bar ch

arted comparison of absolute values co

vered in Top and Bottom Ns.

The bar ch

art expose the range of va

lue covered by Toppers a

nd Bottomers :

-green range is th

e actual sum of monthly va

lue for Bottom Ns ;

-white range is the sum of va

lues of all in

divid

uals that are not in Top Ns nor in Bottom Ns ;

-red range is the sum of va

lues only fo

r individuals in Bottom Ns. That chart helps understa

nd

how overall va

lue has evolved across tim

e, and how much toppers and bottomers h

ave

contributed to it. T

he value indicated on the chart se

ries (w

henmoving mouse over the series) is

the actual amplitude of the series.

Chart 2

displays 3 lines w

ith trended values :

-green line indicates m

inimum value to reach to make it in

the Top Ns ;

-gray dotted line indicates history o

f monthly a

verage value forwhole population

-red line indicates th

e bottom lim

it before falling into Bottom Ns group. That ch

art helps in

fixing

how these lim

its evolve over tim

e, and how far the average groupvalue is from the lim

its.

Chart 3

displays a bar ch

arted percentage comparison of va

lues covered in both Top and

Bottom Ns over tim

e. The color co

ding is s

imilar to other ch

arts. T

his representation is useful to

quickly c

onsider how much of the value, over tim

e, is covered byonly to

ppers a

nd bottomers.

1 -Functio

nal V

alue

The information on this report provides indication of how monthly to

p and bottom aggregate values evolve over tim

e, in comparison with

average of population. This is useful to quickly s

pot variationsin how toppers and bottomers p

erform, and appreciate variationsin the

overall structure of the business. Having this trended insight at a glance can be of dramatic value to help understand structuretrends and

switches, anticipate issues and take prompt correctiv

e actio

ns.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

"D4 Product"."P

01 Product"

"D0 Time"."T

02 Per Name Month" (va

rchar object w

ith

month name)


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "T

rended_Top_N_Limit" (n

umber),

defaults to

: 3,


et the maxim

um Rank lim

it for

individuals to

qualify fo

r Top N and Bottom N ranges

calculations.

This va

riable must b

e defined in a page prompt on the

dashboard page where this report is e

xposed. In the

sample, this p

rompt object is named : "P

rt Trended

TopN".

Specific

Filte

rs


cumulative

ly filte

r out individ

uals that are not within the Top N or

Bottom N lim

it considered. This filte

r is leveraging

group filte


r operators. N

ote that

this filte

r will n

ot im

pact the calculation of the average

for whole population

2 -Layout O

bjects:

The 'S

et N

(Top & Botto

m)top page dashboard prompt allows the user to

set the rank lim

it for Top and Bottom N qualifie

rs in the report. O

ther Prompts

on the dashboard page are filte

ring down the report scope to a choice of

context b

y the user.

3 -Drills

and Navigatio

ns

This p

age has no Drillin


1.5 -Toppers History

This page displays historical information about Top N and BottomN individuals. For each month,

this analysis will in

dicate which individuals were the Top or Bottom N, and, for each, how many

times each of them made it in

the Top or Bottom N during the range of tim

e selected.

1.5 -Toppers In

dividuals H

istory

Chart 1

plots th

e individ

uals in the report according to how frequently th

ey m

ade it in

to Top Ns or

Bottom Ns. T

he Y axis indicates how many tim

e they w

ere toppers,X axis indicates how many

times th

ey w

ere bottomers. The higher on Y axis, the better the performance of the individ

ual over

time. The further rig

ht on X axis, the worst the performance. Individ

uals on top left quadrant

represent regular top performers, w

hile individ

uals on the bottom right quadrant are regular non

performers.

Tables and Chart 2

display counters o

f how many tim

es each listed individ

ual made it in

monthly T

op or Bottom Ns position, over the whole period of tim

econsidered in the report. T

hese

table quickly in

dicate who are the most re

gular Toppers o

r Bottomers, a

nd what exact p

osition

they ra

nk in these group. The list of bar ch

arts respective

ly under each table represent the exact

same information under a bar charted format, to

allow a quicker grasp.

Tables 3$ 4 display detailed information on Top and Bottom for each month inthe period of tim

e

considered. For any given month, the tables will show who was inthe top or bottom Ns positions.

1 -Functio

nal V

alue

The information on this report is

useful to understa

nd who are the individuals that regularly m

ake it in

top or bottom N monthlyindividuals,

over a period of many m

onths. There can be lower business risks w

ith a population where names on monthly to

p N positions are regularly

rotating, versus a situation where the list of monthly to

ppers over a long period of tim

e is very s

hort. S

imilarly B

ottomers that never move

out of the bottom zone are indicative of no relative business improvements and need consideration.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

"D4 Product"."P

01 Product"

"D0 Time"."T

02 Per Name Month" (va

rchar object w

ith

month name)


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "T

rended_Top_N_Limit" (n

umber),

defaults to

: 3,


et the maxim

um Rank lim

it for

individuals to

qualify fo

r Top N and Bottom N ranges

calculations.

This va

riable must b



xposed. In the

sample, this p


rt Trended

TopN".

Specific

Filte

rs


cumulative

ly filte

r out individ

uals that are not within the Top N or

Bottom N lim

it considered. This filte

r is leveraging

group filte


r operators. N

ote that

this filte

r will n

ot im

pact the calculation of the average

for whole population

2 -Layout O

bjects:

The 'S

et N

(Top & Botto

m)top page dashboard prompt allows the user to

set the rank lim

it for Top and Bottom N qualifie

rs in the report. O

ther Prompts

on the dashboard page are filte

ring down the report scope to a choice of

context b

y the user.

3 -Drills

and Navigatio



1.6 -Rank Changes

This page displays information on Top individuals in a dimensionwith a condition upon amplitude of variations

in their ra

nking on a measurement, fro

m one month to another one. The dynamic filte

ring on the report

provides users with the flexibility to

reduce the scope of the analysis to only to

p items with a minimum

variation differential over tim

e.

1.6 -Rank Changes

The 'S

et R

k Varia

tion Lim

it' top page dashboard prompt allows the user to fix th

e minimum

absolute value for ra

nk variations he wants to see in the report. F

or example, se

tting this va

lue to 3

results in

items th

at have increased or decreased their ra

nk by at least 3

positions between current

and last month, or between current and quarter ago month. Any lo

wer ra

nk variations w

ill not

show. This lim

it filtering is applied in addition to the filte

r rule set in the 'Set Top N Limit' to

p page

dashboard prompt block.

The 'S

elect D

imension' d

rop down allows the user to set the detail of dimension detail to

run

the analysis on. In the example, we are looking at top Product in

divid

uals.

Tables and Chart d

isplay actual va

lues of metric per individual for each period, which rank it h

ad

for during that period and how much of a rank variation it e

xperienced from one period to another.

Only in

dividuals which qualify fo

r the filte

red rank variation will show in the list. The table gives the

user the opportunity to

dynamically s

ort th

e content (click on acolumn header in the table to fix th

e

sorting). T

he chart allows to see the variation amplitude on a bar ch

art vis

ual format

1 -Functio

nal V

alue

Perio

d Rank Changes :This re

port is

useful to identify h

ow individ

uals are performing over tim

e in relation to others, and identify

migration trends in

business stru

cture changes. Seasonal or conjectural effects may drive

overall business to

fluctuate up or down, only lo

oking at business

volume may not effective

ly convey underlyin

g changes in

businessstructure. This report allows to spot changes in

how items sta

ck rank among

themselves, and hence makes th

e business stru

cture trends directly vis

ible, outside of se

asonal im

pacts. As an example, while sales fo

r a region may have

been growing over few past p

eriods, it's o

verall ra

nking position against o

ther re

gions m

ay have decreased. From top region, it m

ay now have become

bottom region. Having this information at a glance can be of dramatic value to help identify is

sues and take prompt actions

Year T

o Date Rank Changes : T

his report is

similar to the 'Rank Changes -Period' report, b

ut expresses ranking change over a more significant period of

time (Year To Date) whereas th

e 'Rank Changes -Period' report only c

onsiders o

ne month periods. This ve

rsion of the report is

even less sensitive

than

'Rank Changes -Period' report to

seasonal or conjectural effects th

at drive

business up or down.

4 -Require

d RPD O

bjects

Metric

s :

F1 Revenue"."1


"11 Time Series"."1

-04 Revenue (Month Ago)"

"11 Time Series"."1

-07 Revenue (Quarter Ago)"

Dim

ensional A

ttributes :

"D4 Product"."P

01 Product"


ns :

Presentatio

n Varia

bles

-Variable name : "T

op_N_Limit", d

efaults to

: 10,

used to dynamically s

et the maxim

um Rank lim

it for

individuals to

appear in reports p

opulation.

-Variable name : "R

ank_Var_Limit", d

efaults to

: 3,

used to dynamically s

et the minimum of absolute

value of Rank variation for individ

uals to appear in

reports p

opulation.

Both variables m

ust b

e defined in page prompts o

n


exposed. In

the sample, prompt objects a

re named : "P

rt TopN"

and "Prt R

kVar".

Specific

Filte

rs


cumulative

ly filte

r in individ


it and

within the set Rk Variation. This filte

r is leveraging

group filte


r operators

2 -Layout O

bjects:

The 'S

et T

op N Lim

it' top page dashboard prompt allows users to

fix the

limit of top positions th

ey elect for displaying in the report. T

his filte

r will a

pply

to each period in the report se

t. For example a lim

it set to 'top 5' means to

show any in

divid

ual that made it a

t least once in the top 5, either in current

month, the month before or quarter ago month. The report w

ill then display

the rank variations fo

r this population

3 -Drills

and Navigatio

ns

This p




ill drill d




ill offer


ports (w


only th

e individ

uals clicked)

1.B D

ashboard D

etails

02 History

Analyze tre

nded information, history

and seasonality

2.1 -History

This dashboard page breaks down the metric value over a selectedtime dimension and shows aggregated

values for each period in tim

e : to

tal ye

arly, q

uarterly, m

onthly a

nd weekly, a

s well as average quarterly,

monthly a

nd weekly.

2.0 -History

Chart 1

shows sum of Actual Year va

lue for each period.

Chart 2

shows sum of Actual Quarter va

lue, and code colors each quarter to make them

recognizable year to year

Chart 3

shows sum of Monthly va

lue, along with Monthly a

verage over eachquarter, and

each year. T

hat is, fo

r each year or quarter, how much was the average month sum. The

average value is helpful to understa

nd how business over one quarter ch

anged compared

with other quarters.

Chart 4

is similar to chart 3 but with a grain at the week level : it s

hows sum of each weekly

value, along with weekly va

lue average over each quarter, and each year. T

hat is, for each

year or quarter, how much was the average week sum.

NoteHistorical data may not always have all 12 months of data available for all ye

ars.

Hence, in order for such reports (e

.g., C

hart 1) to still re

turnmeaningful information, the

percentage information needs to

be extra

polated as if 1

2 months of data were available, to

facilita

te compariso

ns across ye

ars.T

he extra

polation implicitly

carried by th

e objects is

one

of basic lin

earity. i.e

., if a year has only 3

months of data, then month percentages of that

year will b

e based on a projected full ye

ar of (12/3)x(s

um of va

lue for the 3 months fo

r which

data is a

vailable).

1 -Functio

nal V

alue

This page helps understand the behavior of a given measure over tim

e. The charts break down the information by Year, Q

uarter,

Month and Week and help get a quick grasp of long term trends in

the value of the measurement. They help understa

nd how a given

period in particular re

lates to the total tre

nd, as well as how periodical averages are impacted.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

"D0 Time"."T

05 Per Name Year"

"D0 Time"."T

03 Per Name Quarter" (T

ext o

bject w

ith

Quarter name)

"D0 Time"."T

02 Per Name Month" (T

ext o

bject w

ith

Month name)

"D0 Time"."T

00 Calendar Date" (D

ate format object)


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

No specific P

resentation Variable necessary fo

r this

report

Specific

Filte

rs

No specific F

ilters n

ecessary fo

r this re

port, b

esides

normal prompted object filte

rs

2 -Layout O

bjects:

3 -Drills

and Navigatio

ns

This p

age has N

avigations enabled : C

licks on metric va

lues and/or

selected chart series will o

ffer navigational menu to jump to other re

ports

(while reducing the scope to only th

e individ

uals clic

ked)

2.1 -Comparativ

e Trending

This dashboard page shows historical representations of a metric, broken down by in

dividuals in a

dimension. It a

llows quick visual comparison of ye

ar on year evolutions for distinct in

dividuals in a dimension.

2.1 -Comparativ

e Trending

Column of C

harts

1shows sum of Actual monthly va

lue, Year over ye

ar for each

individual.

Column of C

harts

2shows cumulated yearly va

lue, per ye

ar, per individ

ual. This chart

helps se

eing how the total ye

ar va

lue builds up for each individ

ual, fo

r each year

Column of C

harts

3shows percent of ye

ar for each month, per individ

ual per ye

ar. T

hat is,

for each month, how much the value for this month represented ofthe total ye

ar va

lue.

Note : H

istorical data may not always have all 12 months of data available for all ye

ars.

Hence, in order for such reports (e

.g., C

hart 1) to still re

turnmeaningful information, the

percentage information needs to

be extra

polated as if 1

2 months of data were available, to

facilita

te compariso

ns across ye

ars.T

he extra

polation implicitly

carried by th

e objects is

one

of basic lin

earity. i.e


months of data, then month percentages of that

year will b


ar of (12/3)x(s

um of va


r which

data is a

vailable).

Pivot ta

ble details(at the bottom) show detail fig

ures fo

r the report, p

er individ

ual.

1 -Functio

nal V

alue

This page helps in understa

nding the behavior of a given measureover tim

e for each year, in

a comparative way over individuals of a

dimension. It a

llows to quickly g

ain understanding of how differently in

dividuals of a dimension perform over tim

e over a selected

metric. T

his chart can easily h

elp spot details of business issues over tim

e that may re

main unnoticed if o

nly lo

oking at aggregate

time value, or aggregate dimensional values.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

"D0 Time"."T

05 Per Name Year"

"D0 Time"."T


ate format object)

"D4 Product"."P

04 Brand"


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

No specific P


r this

report

Specific

Filte

rs

No specific F

ilters n

ecessary fo

r this re

port, b

esides


rs

2 -Layout O

bjects:

3 -Drills

and Navigatio

ns

This p

age has N


licks on metric va

lues in

the table

details will o


ports (while

reducing the scope to only th

e individ

uals clicked)

2.2 -Indexing

This page provides a comparison of se

veral dimension values overa tim

e period using indexed line charts,

as opposed to absolute value line charts

2.2 -Indexing

Chart 1

Displays absolute value compariso

ns fo

r each value in the dimension selected.

Chart 2

Displays the information in an indexed format, using the value for the X axis entered in

prompt block 'Set Index Base' at the top of the page as the basis for the index. F

or example, the

index va

lue is taken from the "Set Index Base " -

all charts w

ill cross th

e 100 red line at this

selected point. E

ach other X axis value is then derive

d from this basis. Update the value in the

top page block and click the GO button to select a

different X value as th

e index basis.

1 -Functio

nal V

alue

This page presents a way to

turn absolute values into indexes and make comparison between trended values a lot easier. It a

llowsusers

to select a value in the X axis, e.g., M

onth, to use as the index basis point. In

dexed information allows users to compare the pattern of

evolution of values in a much easier manner than when using absolute values. Regardless of how far apart th

e absolute values maybe

from one another, in

dexes allow them to be represented in a framed format with comparisons making more visual sense.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

D4 Product"."P

04 Brand"

"D0 Time"."T

05 Per Name Year"

"D0 Time"."T


ext d

escription of

Month)


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "M

onthID_Idx" , d

efaults to

: 2007 /

10,


et the date month used as base

index fo

r the comparison in tim

e analysis.

This va

riable must b



xposed. In the

sample, this p


rt Index

Selector".

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port, b

esides


rs.

2 -Layout O

bjects:

The 'S

et In

dex Basetop page dashboard prompt allows the user to set

which date will b

e set as base 100 for the metric value. Value for every

other date than the one selected as base, will b

e represented asan index to

the value for this b

ase.

3 -Drills

and Navigatio

ns

This p

age has N


licks on metric va

lues and/or



ports


e individ

uals clic

ked)

2.3 -Year S

easonality

by M

onth

This dashboard page provides several views to compare how a specific metric is evolving month to month

over multiple years. It s

hows pattern of monthly v

alues by ye

ar,over se

lected history.

Chart 1

Shows actual va

lue (su

m) for each month across ye

ars. T

his a

llows a quick

understanding of long term trends, a

nd relative

compariso

n year to year.

Chart 2

considers a

ll histo

rical information available in the report andcomputes the contribution

of each month, in percentage terms,to

the yearly to

tal. This c

hart allows to understand the typ

ical

pattern of monthly va

lue distribution over a year.

Chart 3

is similar to chart 2 but co

mpares each year's va

lue to the average value from chart 2

Chart 4

cumulates monthly p

ercentage information and compares each year of histo

ry cumulative

ly. That ch

art allows to better appreciate how variations over months are corrected in

other months fro

m one year to another.

Chart 5

is similar to chart 4 but presenting actual cu

mulative

values. It a

llows to appreciate how

years compare to each other both in their absolute values and their seasonality.

Chart 6

compares actual monthly va

lues fo

r each year

NoteHistorical data may not always have all 12 months of data available for all ye

ars. H

ence, in

order for this re

port to

still return meaningful information, the percentage information needs to

be

extra

polated as if 1

2 months of data were available, to facilita

te comparisons across ye

ars.The

extra

polation implicitly c

arried by th

e objects is

one of basic linearity. i.e


months of data, then month percentages of that ye

ar will b


ar of

(12/3)x(s

um of va


r which data is available).

1 -Functio

nal V

alue

Year S

easonality

by M

onth :The page helps understand monthly s

easonality a

cross years a

ndhow the flow balances across periods

within a year. It c

omputes month values as a percentage of totalye

ar re

venue in a way fa

cilita

ting comparison between years. Italso

helps with a cumulative representation of the full ye

ar, in

dicating the overall pace to completion of the year total. The page can be

useful in forecast and performance measurement processes.

Quarte

r Seasonality

by W

eek and M

onth Seasonality

by D

ay :

These reports are similar to Year Seasonality b

y Month but show different granularitie

s in tim

e dimension

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

"D0 Time"."T


ate format object)

"D0 Time"."T


ext o

bject a

s descrip

tion of Month)

"D0 Time"."T

05 Per Name Year" (N

umber object

Year)


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

No specific P


r this

report

Specific

Filte

rs

No specific F

ilters n

ecessary fo

r this re

port, b

esides


rs

2 -Layout O

bjects:3 -

Drills

and Navigatio

ns

This p

age has N


licks on metric va

lues and/or



ports


e individ

uals clic

ked)

2.3 -Year S

easonality

by M

onth

2.3 -Quarte

r Seasonality

by W

eek

This dashboard page provides several views to compare how a specific metric is evolving Week to Week

over multiple Quarters. It s

hows pattern of monthly v

alues by Q

uarters, over selected history.

2.3 -Month Seasonality

by D

ay

This dashboard page provides several views to compare how a specific metric is evolving day to

day over

multiple Months. It sh

ows pattern of monthly v

alues by M

onths, over selected history.

1.B D

ashboard D

etails

03 Tiering

Insight to help identifying structure

within the layers of value distribution

3.1 -Eighty Twenty

This page displays how the upper tie

r of a specific population set contributes in descending order of va

lue.

The user can dynamically s

et the % lim

it of value that will th

enrender the corresponding % of population that

makes up that va

lue.

3.1 -Eighty Twenty

The S

elect D

imensiondrop down selector (a

t the top) allows users to

run analyses on a different

dimension. For example, if "C

ustomer name" is selected we can look at the top Customers th

at make

up the specific %

of dollars selected in the "Set % Limit" p

rompt. The drop down allows users to

switch

to any m

eaningful other dimensions fo

r this analysis

Chart 1

indicates th

e value split th

at co

mes closest to representing the the user-se

lected value in the

"Set % Limit" p

rompt selectio

n, and shows this in

formation by percentile and ranking of population to

reach that level.

Chart 2

displays a plain pareto chart showing percentile of populationon the X axis and overlays the

percentage of total va

lue. The colored % lines w

ill be determined by th

e user prompt se

lectio

n for 'Set

% Limit'.

Chart 3

shows the cumulative

value by population percentile, and specifically in

dicates in

red the firs

t population percentile where value lim

it selected by user is reached

Chart 4

is similar to Chart 3 but indicates the rank of the first re

cord where cumulative

value

overpasses the value lim

it selected by th

e user.

Chart 5

is similar to Chart 3 but uses deciles in

stead of percentiles, and indicates th

e cumulative

value reached by each decile

1 -Functio

nal V

alue

This report provides users insight on where to focus for a particular analysis. It a

nswers the question "W

hat part of the population should I

focus on to be sure to address th

e most s

ignificant part of the value / problem ?"

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

"D1 Customer"."C

1 Cust N

ame"


ns :

All th

e columns w


nswers


dicate answer calculations

and aggregations for this re

port.

Presentatio

n Varia

bles

Variable name : "C

um_Pct_Limit" (n

umber),

defaults to

: 10,


et the lim

it where report

markers w

ill indicate proportion of population.

This va

riable must b

e defined in a page prompt

on the dashboard page where this report is

exposed. In the sample, this prompt object is

named : "P

rt 8020".

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port,

besides normal prompted object filte

rs.

2 -Layout O

bjects:

The 'S

et %

Lim

it' top page dashboard prompt allows users to

dynamically fix

the level of va

lue significance to highlight in the dashboard page. Setting the %

and clicking on GO will u

pdate all benchmark lines in the reports th

at highlight

the percentage of top population required to reach that va

lue

3 -Drills

and Navigatio

ns

This p

age has N


licks on metric va

lues and/or



ports


e individ

uals clic

ked)

3.2 -Value Based Tierin

g

This page provides a split re

presentation of a population by tie

ring the value of a metric in a given number of

tiers. It ra

nks individuals in descending order, and then groupsthem in buckets of equal value (not equal

counts). T

he report th

en displays the counts per tie

rs, and how other m

etrics distribute according to this

tiering. The number of tie

rs in the report is

dynamically s

et bythe user

3.2 -Value Based Tierin

g

The 'S

elect G

rain' d

rop down selector (a

t the top) allows the user to run the analysis on a

different grain. In the example, the grain is employee, so the tiering will h

appen at the level of

employee. Note that the tiering will b

e constra

ined by th

is granularity, a

s any in

dividual of the

grain selected can only b

elong to one tier at a tim

e.

Default V

iewoffers se

veral graphical representation of the split o

f total va

lue in number of tie

rs.

Tiers va

lues are cut with the grain of population individuals, h

ence the possibility th

at percent

values are not even for each tier. T

he vis

ual representation will d

isplay th

e value and number of

individuals in

each tier, as well as the comparison to an alternative

metric (Metric -2) in the

bottom charts.

Detaile

d data ta

ble available at the top of the page drop down, presents a

n alternative

view

with all detailed records that support th

e vis

ual representations

1 -Functio

nal V

alue

This report is

very u

seful to get a high level idea of how a value distributes across a population. How many customer make up firs

t third of

my re

venue, vs how many in

the second third, vs how many in

the last third. Then how is my profit fo

r the population that composes the

first tie

r of my re

venue ? This report w

ill visually d

isplay th

ese answers a

nd provide with detail ta

bles to show the data.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

"F2 Units"."2

-01 Billed Qty (S

um All)"

Dim

ensional A

ttributes :

"D5 Employee"."E

01 Employee Name


ns :

All th

e columns w


nswers



aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "N

um_of_tiers", defaults to : 3,


et the number of tie

rs to use for

the analysis.

This va

riable must b



exposed. In

the sample, this p

rompt object is n

amed : "P

rt Tiering".

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port, b

esides


rs.

2 -Layout O

bjects:

The 'S

et N

um of T

iers' top page dashboard prompt allows the user to

run the analysis for a different number of tie

rs of va

lue.

3 -Drills

and Navigatio

ns

This p

age has no Drillin

g nor Navigations enabled

3.3 -Boxplot-Whisker

This page provides a comparative analysis on how value of detailrecords distribute, for m

ultiple records of a

dimension. The example shows comparison of standard deviations and volatilitie

s between Products, for

their re

spective population of total revenues by m

arkets

Chart 1

displays boxplotdiagram for each individ

ual in the dimension. The red and green

markers in

dicate bound values of Top and Bottom individuals, th

ered and green lines indicate

the upper lim

it of first d

ecile

, and the lower lim

it of 10th decile. The middle box on the diagram

summarize

s 50% of the population, ie

second and third quartile

. Blue dots in

dicate both average

and median values fo

r each spreads.

Chart 2

displays count information for detailed records in each dimension individual. In

the

example, chart 2 displays how many order in each quarter, fo

r which spread is displayed in chart

1.

Chart 3

displays both boxplotmarkers a

nd volume information (lin

e).

1 -Functio

nal V

alue

It provides a graphical comparative summary o

f a set of data based on the quartile

s of that data set: quartile

s are used to split th

e data

into four groups, e

ach containing 25% of the measurements. T

he boxin the diagram contains 50% of the data, and the extre

mes of that

box are the Q1 and Q3 quartile

s: the median value of the data set is th

e Q2, second quartile

, value. Each whiskerre

presents 25% of the

data and the extre

mities of these whiskers a

re the minimum and maxim

um values of the data. This report provides users insight onwhere

to focus fo

r a particular individual of a dimension. It h

elps understanding structural differences in how data spreads betweemindividuals

of a dimension. For example, looking at all orders d

etails for each region, seeing what are values for each region of : sm

allestorder, first

quartile

limit order, m

edian order, to

p quartile

limit order andlarges order. T

he chart allows quick visual comparison of each region

distribution with each other.

As another example, it c

an be used to display stock prices variations for each day : o

pening Value, high value, low value, closevalue

during a certain tim

e period. Additionally th

e chart can show volume for each day.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1

-01 Revenue (S

um All)

Dim

ensional A

ttributes :

" D0 Time"."T

03 Per Name Qtr"

"D3 Order"."O

0 Order Key"


ns :

Many columns in

this report re

ly on answers b

ased

calculations and aggregations.

Presentatio

n Varia

bles

No specific P


r this

sample report

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port, b

esides


rs.

2 -Layout O

bjects:

The 'S

elect D

etails

to analyze'drop down (at the top) allows users to

change detail of

records being analyze

d. For example, if "C

1 Customer name" is selected, the report w

ill display spread of cu

stomer re

venue for each quarter comparative

ly.

3 -Drills

and Navigatio

ns

This p

age has N


licks on Dimension values w

ill offer navigational menu to jump to other re

ports (w

hile reducingthe

scope to only th

e individ

uals clicked).

3.3 -Boxplot-Whisker

3.4 -Waterfa

ll Single Dim

ension

This page shows how an initial value is increased and decreased by a series of intermediate values, leading

to a final total value. An invisible column keeps the increases and decreases linked to the heights of the

previous columns.

3.5 -Waterfa

ll Double Dim

ension

This page Shows how an initial value is increased and decreased by a series of intermediate values,

breaking down details of dimension individuals for each intermediate value.

3.6 -Decilin

g Comparativ

e

This page displays a comparative analysis between several metrics, each displayed and ordered according

to the deciling of a selected single metric. S

pecifically, w

ith customer re

venue as reference for deciling, see

how cost, profit, s

ervic

e and price metrics each distribute by single customer re

venue decile. W

ith such

analysis, interesting conclusions can be seen, for instance the customers in the highest re

venue decile may

not be the top most profitable customers.

3.6 -Decilin

g Comparativ

e

The 'S

elect P

opulatio

n to

Analyze' drop down selector (a

t the top) allows the user to set the

dimension detail to

run the analysis on, i.e

., what individ

ual population will th

e deciles be

calculated for? Customers? Orders? Batches? Calls? In the example, we are looking at

Customer individ

uals.

Chart 1

displays plain bar chart distribution of 're

ference metric' (m

etric -1) actual va

lues per

selected dimension individ

ual deciles. T

he values are indicated as percentage of cu

mulated total,

in order to allow for easier re

adability. T

he red marker indicates an average value (10%). T

he

table below the chart sh

ows value for each decile as w

ell as count of distinct individ

uals in each

decile.

Chart 2

displays distribution of percentage of totals for m

etric -

2 values. T

he X axis of ch

art still

shows the deciles of Metric -1, but only n

ow the Y axis indicates sp

lit on metric -

2 values.

Chart 3

is similar to Chart 2, but displays % of Metric -3 distributed by M

etric -1 deciles.

Chart 4

is similar to Chart 2, but displays % of Metric -4 distributed by M

etric -1 deciles.

Chart -

5 (at bottom of the page) plots the values of the deciles according to how much they

represent of metric -1, metric -2

and metric -

3. A diagonal representation on this c

hart re

flects

that va

lues are proportionally d

istributed for each metrics, according to the deciles of Metric -

1.

Example : cu

stomers w

ho generate the highest re

venue would generate the highest p

rofit to

o

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1


"F3 Bookings"."4

-01 Booked Qty (S

um All)"

"F2 Units"."2

-01 Billed Qty (S

um All)"

"F3 Bookings"."3

-01 Booked Amt (S

um All)"

Dim

ensional A

ttributes :

D1 Customer"."C

1 Cust N

ame"


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "N

value_for_Ntilin

g", defaults to

: 10,


et the number of tile

s to use for

the analysis.

This va

riable must b



xposed. In the

sample, this p


rt Ntilin

g".

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port, b

esides


rs.

2 -Layout O

bjects:

The 'S

et N

um of T

iles' top page dashboard prompt allows the user to

run the analysis with a different number of tile

s than 10, to see finer or

less granular analysis.

3 -Drills

and Navigatio



1 -Functio

nal V

alue

This comparative report provides key in

formation about how 'wellbalanced' business metrics can be between each others. T

he key concept

is to look at several aspects o

f business, with the lens of a dimension deciling on that single metric. "L

et me order my customers by deciles

according to a specific metric, for instance revenue, and then show me all other selected metrics

against each revenue decile groups of

customers". T

his report is

particularly u

seful to quickly s

pot atwist in business structure and to allow intelligent investigations on underlyin

g

causes. T

his report w

ill give oriented insight and help take action to influence interdependency of business metrics between each other (ris

k with profit, re

venue with cost, e

tc). It can also be useful to understand changes in metrics in

terdependency across tim

e : A

re my to

p / bottom

deciles customer similar to last ye

ar ? If n

ot, w

hat is the correlated behavior of underlyin

g business metrics th

at ca

n explain that ? Pricing,

Volume, Service Quality... H

aving this information at a glance can be of dramatic v

alue to help identify is

sues and take prompt actions.

1.B D

ashboard

Details

04 Distribution

Several simple statistical distribution

representation of detailed datasets

4.1 -Statis

tical D

istrib

utio

n

This page provides basic statistical discrete distribution viewsof a selected population. It le

ts the user

dynamically d

efine the number of buckets to

use for statistical distribution, as well as the grain in the

population, and provides with several dynamic representations ofthe results

4.1 -Statis

tical D

istrib

utio

n

The 'S

elect G

rain of A

nalysis' drop down selector (a

t the top) allows the user to run the

analysis on a different grain. In the example, we are looking atcustomer individual dollars

distribution, ie how total sa

les for each of my product sp

read between min one and max one.

Changing the dimension allows to switch to any other meaningful dimensions fo

r this analysis

Chart 1

shows a bar chart of the value distribution. Y axis for the bar is h

ow much percentage

each bucket represents of the total amount. The overriding line indicates cu

mulative

percentages

of the value. The x a

xis of this chart in

dicates th

e calculated min and the max va

lue of each

bucket.

Chart 2

is similar to chart 1, but plots o

ccurrences counts a

s opposed to value. The bar chart

indicates th

e count of distin

ct individ

uals in each bucket, and is re

presentative

of a probability to

fall in

each bucket. The x a

xis of this c

hart in

dicates the number of the bucke

t. To see the

calculated min and the max va

lue of a bucket number, re

fer to the table below the charts.

Chart 3

shows value percentage distrib

ution, and highlights th

e confidence interval lim

its in

each bucket. Ie

what is the cumulated likelihood that an individ

ual falls under the upper lim

it of

that interval.

Lim

itatio

nThis c

urrent ve

rsion of the report is

not able to display 'e

mpty b

ins'. Ie

, as th

e reports

calculates th

e number of buckets sp

ecified by th

e use, if n

o occurrence fall in

a specific bucket,

then this one will n

ot be vis

ible on the report at all. T

his d

oes not im

pact th

e calculations sh

own in

the report, b

ut does impact the vis

ual aspect of the distribution charts. T

his lim

itation can be fixe

d

by adding a 'Union' query to

this a

nswers definition, with a firm

numbering of each bucket in it.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1


Dim

ensional A

ttributes :

D1 Customer"."C

1 Cust N

ame"


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "N

umBands", d

efaults to

: 15,


et the number of fixe

d bins to

use for the distribution analysis.

This va

riable must b



xposed. In the

sample, this p


rt Distribution".

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port, b

esides


rs.

2 -Layout O

bjects:

The 'S

et #

of b

ins' top page dashboard prompt allows the user to

dynamically fix th

e number of bins th

at the analysis should use.Setting this

number to 20 and hittin

g go will u

pdate all re

ports w

ith a new calculated x

axis.

3 -Drills

and Navigatio



1 -Functio

nal V

alue

This report is

useful to understand how the individuals of a population spread between the min and the max values, and to infer the

probabilitie

s for an individual to fall in

a specific bucket. The report applies to numerous business areas : distribution of order values,

distribution of call tim

es, distribution of salaries... a

nd allow to visually a

ppreciate skeweness of a given population versus typ

ical distribution

that may be expected.

4.2 -Comparativ

e D

istrib

utio

n

This page provides a comparative representation of statistical distribution views for a selected population. In the

example, it s

hows a compariso

n of va

lue distributions by customers over a number of brands. The user can

dynamically d

efine the number of buckets to

use for statistical distribution, as well as the grain of the population.

4.2 -Comparativ

e D

istrib

utio

n

The 'S

elect G

rain of A



analysis on a different grain. In the example, we are looking atcustomer individual dollars

distribution, ie how total sa

les for each of my product sp

read between min one and max one.

Changing the dimension allows to switch to any other meaningful dimensions fo

r this analysis

The 'S

elect C

omparativ

e Serie

s' allows users to

run the comparative

analysis on comparative

dimensions other than year.

Chart 1

shows a bar chart of the value distribution by co

mparative

dimension. The Y axis

indicates th

e sum of metric value represented by each bucket. The line series in

dicates th

e

distinct va

lues of the comparative

dimension. The X axis of thischart in

dicates the calculated

minimum and maxim

um values of each bucket.

The Comparativ

e Charts

columns (rig

ht of screen) sh

ow value distrib

ution and occurrence

count distributions for each value of the comparative

dimension.This vis

ualiza

tion allows users to

clearly c

ompare several va

lues of the comparative dimension.

Chart 2

is similar to Chart 1, but plots th

e count of occurrences as opposed to the value of

them. The Y axis indicates the count of distinct in

divid

uals in each bucket.

Chart 4

and 5are comparative

distribution histograms fo

r each year, re

spective

ly showing

counts a

nd values distributions

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1


Dim

ensional A

ttributes :

D1 Customer"."C

1 Cust N

ame

D4 Product."P

04 Brand"


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "N

umBands", d

efaults to

: 15,



d bins to


This va

riable must b



xposed. In the

sample, this p


rt Distribution".

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port, b

esides


rs.

2 -Layout O

bjects:

The 'S

et #

of b

ins' top page dashboard prompt allows the user to

dynamically fix th

e number of bins th

at the analysis should use.Setting this

number to 20 and hittin

g go will u

pdate all re

ports w

ith a new calculated x

axis.

3 -Drills

and Navigatio

nsThis page has Hierarchical Drillin

g enabled : clicks on

dimension values w

ill drill d


1 -Functio

nal V

alue

This report highlights how the spread of value tiers c

hanges fro

m one value of a dimension to another one (e.g., fro

m one year to another).

The report can help explain why performance is different fro

m one case to another, or has changed from one year to another by showing the

structural distribution changes in the population of events. F

orexample, the evolution of mix o

f order values from large to sm

all, c

hange

from one region to another for the distribution of call durations, salaries, et al.

4.3 -Varia

bility

Analysis

This page provides sim

ple view of extre

me and middle percentilesof metric values in a population. It s

hows the top and bottom

5 percentiles, the middle 3 percentiles, as well as top and bottom ranker va

lues.

4.3 -Varia

bility

Analysis

The 'S

elect G

rain of A



analysis on a different grain. In the example, we are looking order individ

uals value distribution

Main hart 1

shows a bar ch

art re

presentation of the values fo

r each extre

me and middle

percentile. Percentile 50 will b

e representative

of the average horizo

ntal bar of the value

distribution.

Tables next to

the chart in

dicate detailed values (sum and Avg) for each percentile, as w

ell as

the absolute values fo

r the top and bottom performers.

4 -Require

d RPD O

bjects

Metric

s :

"F1 Revenue"."1


Dim

ensional A

ttributes :

"D3 Order"."O

0 Order Key"


ns :

All th

e columns w


nswers Calc'

in the report in


aggregations fo

r this re

port.

Presentatio

n Varia

bles

Variable name : "N

tile_Limit_Filter" (n

umber), d

efaults

to : 5,



d bins to


This va

riable must b



xposed. In the

sample, this p


rt Percentiles".

Specific

Filte

rs

No specific F

ilters n

ecessary to

this re

port, b

esides


rs.

2 -Layout O

bjects:

The 'S

et P

ercentile

s' top page dashboard prompt allows the user to

dynamically fix th

e number of extre

me percentiles that sh

ould be

displayed in the analysis

3 -Drills

and Navigatio



1 -Functio

nal V

alue

This report is

useful to quickly u

nderstand how spread a population is between its min, avg and max values for a metric. lo

okingat this

report w

ill help get an idea of the distance between toppers group from average, and from bottom. The report also provides simple table with

discrete view on top/bottom individuals values.

4.4

Scatte

r & Boxplot

This page provides a simple graphical su

mmary o

f a set of data. Displays both scattered detail of each

individuals in the set of data and shows measures of central median, dispersion and skewness.

4.5 -Standard Deviatio

n Comparativ

e

This page provides a comparative standard deviation analysis on a metric for a selected set of populations.

The example shows compariso

n of standard deviations and volatilitie

s between Products, for th

eir re

spective

population of total revenues by m

arkets

4.5 -Standard Deviatio

n Comparativ

e

The 'S

elect le

vel o

f detail fo

r each in

dividual' drop down selector (a

t the top) allows the user to

set the detail of population for which Product c

omparative

analysis will b

e run. In the example, the set

of Market means that, fo

r each Product, re

spective

population ofmarket revenues will b

e considered

and Standard Deviation measured upon it. T

hen the report w

ill compare all th

e respective

results

between Products.

Chart 1

plots th

e comparison of Average values and Standard Deviation for each comparative

dimension individ

ual. The green and blue lines in

dicates Averagefor this in

divid

ual plus and minus

once the Std Dev va

lue. The amplitude between the lines gives anindication of where occurrences

may fa

ll for this c

omparative

dimension individ

ual. The x a

xis is sorted on ascending total va

lue per

individual. The red tria

ngle marker on x a

xis indicates the top sta

ndard deviation values. T

he orange

square marker on x a

xis indicates th

e top volatility d

eviation values.

Chart 2

shows a representation of Total va

lue per individ

ual, along witha volatility in

dicator (g

rey

bar) in

%. This ch

art allows to appreciate how standard deviation ranges co

mpared to average value

for each individ

ual, and where this individ

ual ranks in

the ascending total order. T

he x a

xis is sorted

on ascending total va

lue per individual. The red tria

ngle markeron x a

xis indicates th

e top standard

deviation values. T

he orange square marker on x a

xis indicates th

e top volatility d

eviation values.

Quadrant C

hart 3

plots th

e individ

uals against tw

o axis : to

tal va

lue of metric (y), vo

latility (x). T

he

top righ

oracle bi sample app v1.2

Documents

reports details

n individuals

dashboards overviewoverview

topperstop individuals

frequency of individuals

trended benchmarking5

year seasonality

typical reports examples