H2O World - PAAS: Predictive Analytics offered as a Service - Prateem Mandal

MarketShare confidential and proprietary 1

Predictive Analytics as a Service

Prateem Mandal, Tech Lead Architect

November 02, 2015


MarketShare: A Decade of Decision Enablement 20-30% increase in marketing efficiency, 3-4% increase in revenue, 10-50% ROI

Proprietary analytical techniques fuse

market level, consumer and CRM

techniques

100+ Data Scientists and PhDs with

operational modeling experience

10 Patents and 36 patents pending

for applied modeling and technology

Science & Math Application Enablement

70K Scenarios generated by clients in

2014

Predictive modeling on 10’s of TB of

data per customer

1,000+ active users

Global CMO network

Experience deploying

technologies at over 100

Fortune 500 companies

Deep strategic

partnerships


Analytics Life Cycle

1 New Client

Model UAT

Onboarding

Scoring &

Attribution Modeling

Scenario

Analysis &

Reporting Feature

Engineering

ETL



1 New Client

Model UAT

Attribution

Funnel

creation

Post

Processing

Modeling

Feature Set

Transformed

Modeling

Feature Set

Feature

Engineering

Configs

ETL

Configs

Model UAT

Automated

Modeling

Onboarding

Scoring &


Scenario

Analysis &

Reporting Feature

Engineering

ETL



1 New Client

Model UAT

Modeling

Feature Set

Transformed

Modeling

Feature Set

Onboarding

Scoring &


Scenario

Analysis &

Reporting Feature

Engineering

ETL

E F F E C T

L O O K B A C K

C A U S E

U S E R S E Q U E N C E

U S E R

Conversion

PURCHASE

Online Events Offline Events Past Activity

E F F E C T

L O O K B A C K

C A U S E


U S E R

Online Events Offline Events Past Activity

EMAIL SEARCH DISPLAY NEWSPAPER TV ACTIVITY

Conversion

PURCHASE

E F F E C T C A U S E


U S E R

CHANNEL

Conversion

PURCHASE



U S E R

CHANNEL

SUB CHANNEL EMAIL BRAND

AUDIO

BRAND

VIDEO BRAND

NON

BRAND

NON

BRAND

BRAND

VIDEO

BRAND

VIDEO

Conversion

PURCHASE



U S E R

CHANNEL

SUB CHANNEL

TACTIC

Conversion

PURCHASE

EMAIL BRAND

AUDIO

BRAND

VIDEO BRAND

NON

BRAND

NON

BRAND

BRAND

VIDEO

BRAND

VIDEO

EMAIL TARGETING UNKNOWN CON PLA TARGETING NON

TARGETING TARGETING



U S E R

CHANNEL

SUB CHANNEL

TACTIC

Conversion

PURCHASE

EMAIL BRAND

AUDIO

BRAND

VIDEO BRAND

NON

BRAND

NON

BRAND

BRAND

VIDEO

BRAND

VIDEO


TARGETING TARGETING

L O O K B A C K



U S E R

CHANNEL

SUB CHANNEL

TACTIC

Conversion

PURCHASE

EMAIL BRAND

AUDIO

BRAND

VIDEO BRAND

NON

BRAND

NON

BRAND

BRAND

VIDEO

BRAND

VIDEO


TARGETING TARGETING

L O O K B A C K

ATTRIBUTION

88%

C A U S E E F F E C T U S E R


CHANNEL

PURCHASE L O O K B A C K



L O O K B A C K



L O O K B A C K

E F F E C T U S E R

A G G R E G A T E D U S E R S E Q U E N C E

M E T R I C i M E T R I C 1 M E T R I C 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

CHANNEL


𝑮𝑯𝑻 𝒙𝒊 =𝟏

𝟏 +𝐦𝐢𝐧(𝒙𝒊)

U S E R E F F E C T C A U S E







5

7

13






5

7

13

E F F E C T U S E R M E T R I C i M E T R I C 1 M E T R I C 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13 7 5






5

7

13


13 7 5





𝟏

𝟏 +𝐦𝐢𝐧(𝟏𝟑, 𝟕, 𝟓)

E F F E C T M E T R I C i M E T R I C 1 M E T R I C 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . U S E R


5

7

13


13 7 5





𝟏

𝟔



5

7

13


13 7 5





𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕



1 New Client

Model UAT

Attribution

Funnel

creation

Post

Processing

Onboarding

Scoring & Attribution Modeling

Scenario Analysis & Reporting

Feature Engineering

ETL


𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕

E F F E C T M E T R I C i M E T R I C 1 M E T R I C 2 U S E R


𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕


𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕


𝟎 𝟎. 𝟗𝟗𝟗𝟗𝟗𝟗 𝟏 𝟏 𝟎


𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕


𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕


𝟎 𝟎. 𝟗𝟗𝟗𝟗𝟗𝟗 𝟏 𝟏 𝟎

0.88 0.35 0.41 0.12


𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕


𝟎. 𝟏𝟔𝟔𝟔𝟔𝟔𝟕


𝟎 𝟎. 𝟗𝟗𝟗𝟗𝟗𝟗 𝟏 𝟏 𝟎

M E T R I C S E F F E C T U S E R A T T R M- A T T R

0.88

0.88 0.35 0.41 0.12


1 New Client

Model UAT

Attribution

Funnel

creation

Post

Processing

Onboarding



Feature Engineering

ETL



0.88

C A U S E E F F E C T U S E R A T T R M- A T T R E- A T T R



0.117

0.117

0.117

0.35

0.88

0.88




0.000

0.000

0.350

0.35

0.88

0.88




0.35

0.41

0.12

0.88

0.88

C A U S E E F F E C T U S E R E- A T T R




U S E R

CID Channel Campaign Tactic

E1 DISPLAY BRAND VIDEO TARGETING


E3 DISPLAY BRAND VIDEO NON TARGETING

E4 SEARCH BRAND UNKNOWN

E5 SEARCH NON BRAND CON

E6 SEARCH NON BRAND PLA

E7 STORE NEWS --

ATTR

.05

.20

.10

.18

.08

.15

.12

SID Geo Zip

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

EID Product Brand Group

A1 Prod1 Brand1 Group1








M E A S U R E S








E7 STORE NEWS --

ATTR

.05

.20

.10

.18

.08

.15

.12

SID Geo Zip

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123












U S E R

Channel Campaign

DISPLAY BRAND VIDEO

DISPLAY BRAND VIDEO

DISPLAY BRAND VIDEO

SEARCH BRAND

SEARCH NON BRAND

SEARCH NON BRAND

STORE NEWS

ATTR

.05

.20

.10

.18

.08

.15

.12

Geo

NA

NA

NA

NA

NA

NA

NA

Product Brand

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1


Reporting dimensions

M E A S U R E S

M E A S U R E S








E7 STORE NEWS --

ATTR

.05

.20

.10

.18

.08

.15

.12

SID Geo Zip

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123












U S E R

Channel Campaign

DISPLAY BRAND VIDEO

SEARCH BRAND

SEARCH NON BRAND

STORE NEWS

ATTR

.35

.18

.23

.12

Geo

NA

NA

NA

NA

Product Brand

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1



M E A S U R E S

M E A S U R E S








E7 STORE NEWS --

ATTR

.05

.20

.10

.18

.08

.15

.12

SID Geo Zip

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123

U1 NA 123












U S E R

M E A S U R E S

Channel Campaign

DISPLAY BRAND VIDEO

SEARCH BRAND

SEARCH NON BRAND

STORE NEWS

ATTR

.35

.18

.23

.12

Geo

NA

NA

NA

NA

Product Brand

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1

Prod1 Brand1


M E A S U R E S


SPEND

10.5

8.33

2.75

14.85

39

40

41

42

43

44

Analytics Life Cycle – Engineering Aspects

1 New Client

Model UAT

Attribution

Funnel

creation

Post

Processing

Modeling

Feature Set

Transformed

Modeling

Feature Set

Feature

Engineering

Configs

ETL

Configs

Model UAT

Automated

Modeling

Onboarding



Feature Engineering

ETL


stack_parameters.xml

stack_transforms.xml

stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>

<name>EVT_MARKETING_SEG_DIMS_SET</name>

<elements>

<elements><attribute>channel_type</attribute><value>“Display”</value></elements>

</elements>

<elements>

<elements><attribute>channel_type</attribute><value>“Paid Search”</value></elements>

</elements>

</set>

<select>

........

<param>METRICS_EVTSTACK</param>

........

</select>

........

<set name="EVT_MARKETING_SEG_DIMS">

<attr>channel_type</attr>

</set>

#!/bin/bash ................. cmdstatus=`java -jar ${codegenerator_jar_dist_loc}/${code_generator_jar_name} -s ${common_stages_loc}/$PHASE_NAME -d ${script_loc}/$PHASE_NAME -c $input_schema_config_loc -g $code_generator_grammar_loc` .................

OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5

stack_gen_config.xml

2


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>

<name>HASDONEBEFORE</name>

<defn>.....</defn>

</metric>


<metric>


<defn>.....</defn>

</metric>

CREATE TABLE stackevtterms

AS

SELECT

.. AS stackmetric_hasdonebefore_event_display,

.. AS stackmetric_hasdonebefore_event_paidsearch,

......

FROM

...... <set name="EVT_STACKMETRICS">

<val enable=“TRUE">HASDONEBEFORE</val>

<val enable=“FALSE">NUM</val>

</set>

#!/bin/bash ................. cmdstatus=`hive –f $PHASE_NAME.hql` .................

6

Input Config

Generated Config



1 New Client

Model UAT

Model UAT

Automated

Modeling

Onboarding

Scoring &


Scenario

Analysis &

Reporting Feature

Engineering

ETL


Modelling Spec • Initial set

of variables • Business

rules

Model

Build N Choice Models

Model Evaluation and Ranking • Business Rules • Goodness of Fit • Statistical diagnosis

Finalized Model

Population Generational Iteration • Top models cross –over to

generate offspring models • Variable mutation

• Bayesian priors • Coeff bounds • Attribution bounds

Attribution

Stack

Automated Model Search – A Genetic Algorithm Approach


Max of modelScore Model Source

Iterations CrossOver Mutation New Max Score

1 0.814674133 0.814674133

2 0.840250827 0.874642259 -0.142370371 0.874642259

3 0.86051811 0.843359676 0.726339045 0.86051811

4 0.861854898 0.850294643 0.434102915 0.861854898

5 0.868137103 0.851901188 0.709897779 0.868137103

6 0.890517983 0.873505914 0.835870771 0.890517983

7 0.890538416 0.857600064 0.538250044 0.890538416

8 0.900386103 0.877312775 0.389444869 0.900386103

9 0.896563775 0.861402806 0.227565829 0.896563775

10 0.893281436 0.866702979 0.429202581 0.893281436

11 0.907564542 0.869666755 0.738092262 0.907564542

12 0.904108687 0.887093232 0.850036487 0.904108687

13 0.904159874 0.884415807 0.860378596 0.904159874

14 0.905516755 0.898474717 0.4425833 0.905516755

15 0.911024584 0.904605785 0.776345059 0.911024584

16 0.911007328 0.905694898 0.496509904 0.911007328

17 0.910692312 0.898231697 0.815998341 0.910692312

18 0.895302999 0.901081899 0.45632258 0.901081899

19 0.907471425 0.860367793 0.675483196 0.907471425

20 0.904312199 0.872822381 0.787050984 0.904312199

Max Score 0.911024584 0.905694898 0.860378596 0.911024584

GA Progression over Iterations

Model with Max Score is generated from {Cross-Over, Mutation} and not from {New}


0.8

0.82

0.84

0.86

0.88

0.9

0.92

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Mo

del

Sco

re

Iterations

C

C

Cross-Over Model Score by Iterations

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Mo

del

Sco

re

Iterations C - Average of modelScore C - StdDev of modelScore


Model Score Improvement for Cross-over models over Iterations

-0.800

-0.600

-0.400

-0.200

0.000

0.200

0.400

0.600

0.800

1.000

1 3 5 7 9

11

13

15

17

19

21

23

25

27 29 31

33

35

37

39 41 43

45

47

49

51 53 55

57

59

61

63

65

67

69

71

73

75

77

79

81

83

85

87

89

91

93

95

97

99

101

103

105

107

109

111

113

115

117

119

121

123

125M

od

el S

core

Models over Iterations



1 New Client

Model UAT

Attribution

Funnel

creation

Post

Processing

Modeling

Feature Set

Transformed

Modeling

Feature Set

Feature

Engineering

Configs

ETL

Configs

Model UAT

Automated

Modeling

Onboarding

Scoring &


Scenario

Analysis &

Reporting Feature

Engineering

ETL


Analytics Life Cycle - Numbers

1 New Client

Model UAT

Attribution

Funnel

creation

Post

Processing

Modeling

Feature Set

Transformed

Modeling

Feature Set

Feature

Engineering

Configs

ETL

Configs

Model UAT

Automated

Modeling

Onboarding

Scoring &


ETL

Scenario

Analysis &

Reporting Feature

Engineering

0-2 w 2 d

2 h

4 h

.5 h

25 h

1 d 3 h

1.5h

2 h


Questions &

Discussion


Additional

Engineering

Slides




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>


</elements>

<elements>


</elements>

</set>

<select>

........


........

</select>

........



</set>


OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5


2


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>


<metric>


<defn>.....</defn>

</metric>


AS

SELECT



......

FROM




</set>


6

Input Config

Generated Config




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>


</elements>

<elements>


</elements>

<elements>

<elements><attribute>channel_type</attribute><value>“Organic Search”</value></elements>

</elements>

</set>

<select>

........


........

</select>

........



</set>


OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5


2


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>


<metric>


<defn>.....</defn>

</metric>


AS

SELECT



.. AS stackmetric_hasdonebefore_event_organicsearch,

......

FROM




</set>


6

Input Config

Generated Config

Data change




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>


<elements><attribute>evt_sub_channel</attribute><value>“Online Display”</value></elements> </elements>

<elements>


<elements><attribute>evt_sub_channel</attribute><value>“Direct Response Video”</value></elements>

</elements>

<elements>


<elements><attribute>evt_sub_channel</attribute><value>“Brand”</value></elements>

</elements>

<elements>


<elements><attribute>evt_sub_channel</attribute><value>“Unknown”</value></elements>

</elements>

</set>

<select>

........


........

</select>

........



<attr>evt_sub_channel</attr>

</set>

OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4


2


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>


<metric>


<defn>.....</defn>

</metric>


AS

SELECT

.. AS stackmetric_hasdonebefore_event_display_onlinedisplay,

.. AS stackmetric_hasdonebefore_event_display_directresponsevideo,

.. AS stackmetric_hasdonebefore_event_paidsearch_brand,

.. AS stackmetric_hasdonebefore_event_organicsearch_unknown,

......

FROM

......

<set name="EVT_STACKMETRICS">



</set>


6

Input Config

Generated Config

Adding segmentation dimension

#!/bin/bash ................. cmdstatus=`java -jar ${codegenerator_jar_dist_loc}/${code_generator_jar_name} -s ${common_stages_loc}/$PHASE_NAME -d ${script_loc}/$PHASE_NAME -c $input_schema_config_loc -g $code_generator_grammar_loc` ................. 5




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>



<elements>



</elements>

<elements>



</elements>

<elements>



</elements>

</set>

<select>

........


........

</select>

........




</set>


OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5


2


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>


<metric>


<defn>.....</defn>

</metric>

<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>


AS

SELECT





.. AS stackmetric_num_event_display_onlinedisplay,

.. AS stackmetric_num_event_display_directresponsevideo,

.. AS stackmetric_num_event_paidsearch_brand,

.. AS stackmetric_num_event_organicsearch_unknown,

......

FROM

......



<val enable=“TRUE">NUM</val>

</set>


6

Input Config

Generated Config

Selecting NUM metric




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>



<elements>



</elements>

<elements>



</elements>

<elements>



</elements>

</set>

<select>

........


........

</select>

........




</set>


OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5


2


<metric>


<defn>.....</defn>

</metric>

<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>


AS

SELECT









.. AS stackmetric_gsm90_event_display_onlinedisplay,

.. AS stackmetric_gsm90_event_display_directresponsevideo,

......

.. AS stackmetric_gsm365_event_paidsearch_brand,

.. AS stackmetric_gsm365_event_organicsearch_unknown,

......

FROM

......




<val enable=“TRUE">GSM</val>

</set>


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>

Input Config

Adding new metric


6

Generated Config

<set name= “GSM_STEP">

<val>90</val>

<val>180</val>

<val>365</val>

</set>




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>



<elements>



</elements>

<elements>



</elements>

<elements>



</elements>

</set>




</set>


OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5


2


<metric>


<defn>.....</defn>

</metric>

<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>


AS

SELECT









.. AS stackmetric_gsm_event_display_onlinedisplay,

.. AS stackmetric_gsm_event_display_directresponsevideo,

.. AS stackmetric_gsm_event_paidsearch_brand,

.. AS stackmetric_gsm_event_organicsearch_unknown,

......

FROM

......





</set>


<val>3</val>

</set>

Input Config

Adding new metric


6

Generated Config

stackevtterms_(<STCKGEN_RP><SDATE>i)

-- This query calculating all the NUM event metrics (stack variables or stack metrics).

-- stackevtterms_<RP_START_i> is created separately for each of the RP with RP_START in its name

DROP TABLE stackevtterms_(<STCKGEN_RP><SDATE>i);

CREATE TABLE stackevtterms_(<STCKGEN_RP><SDATE>i) AS

SELECT

<METRICS_EVTSTACK>

<OTHER_METRICS_EVTSTACK> t2.rp_start AS rp_start,

t2.rp_end AS rp_end,

t1.userid AS userid,

t1.actuuid AS actuuid,

t1.<ACTIVITYGROUP> AS <ACTIVITYGROUP>,

t1.refdate_rp AS refdate_rp,

t1.response AS response

FROM tmpUsersActivityDate_(<STCKGEN_RP><SDATE>i) t1 LEFT OUTER JOIN elbis_(<STCKGEN_RP><SDATE>i) t2

ON (t1.userid = t2.userid)

WHERE (t1.sample_flag = 1)

GROUP BY t2.rp_start, t2.rp_end, t1.userid, t1.actuuid, t1.<ACTIVITYGROUP>, t1.refdate_rp, t1.response;


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>

<select>

........


........

</select>

........




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>



<elements>



</elements>

<elements>



</elements>

<elements>



</elements>

</set>




</set>


OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5


2


<metric>


<defn>.....</defn>

</metric>

<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>


AS

SELECT













......

FROM

......





</set>


<val>3</val>

</set>

Input Config

Adding new metric


6

Generated Config






SELECT

<METRICS_EVTSTACK> <OTHER_METRICS_EVTSTACK> t2.rp_start AS rp_start,












<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>

<select>

........


........

</select>

........


SUM(1 / (1 + DATEDIFF( refdate_rp CASE WHEN (

(channel_type IN ('Display') AND evt_sub_channel IN ('Online Display')) AND (evt_time > refdate_rp - (60 + 1) AND evt_time <= refdate_rp) ) THEN evt_time ELSE null END

)/365 )

) AS stackmetric_gsm365_event_display_onlinedisplay,


<and> <xprod> <in>

<xprodlist>EVT_MARKETING_SEG_DIMS_SET<element>attribute</element></xprodlist> <xprodlist>EVT_MARKETING_SEG_DIMS_SET<element>value</element></xprodlist> </in> </xprod> </and> AND (evt_time > refdate_rp - (60 + 1) AND evt_time <= refdate_rp) ) THEN evt_time ELSE null END

) / <val>GSM_STEP</val> )

) AS stackmetric_gsm<val>GSM_STEP</val>_event_<xprod><xprodlist>EVT_MARKETING_SEG_DIMS_SET<element>value</element></xprodlist></xprod>,




stack.hql

Code

Generator

BaaS

Config

Generator

stack_gen.sh

<set>


<elements>



<elements>



</elements>

<elements>



</elements>

<elements>



</elements>

</set>




</set>


OR

CH

ES

TR

AT

ION

RUN

GET

PUT

ACTION

BACKEND

1

3

4

5


2


<metric>


<defn>.....</defn>

</metric>

<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>


AS

SELECT













......

FROM

......





</set>


<val>3</val>

</set>

Input Config

Adding new metric


6

Generated Config


<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>.....</defn>

</metric>






SELECT

<METRICS_EVTSTACK> <OTHER_METRICS_EVTSTACK> t2.rp_start AS rp_start,












<metric>

<name>NUM</name>

<defn>.....</defn>

</metric>

<metric>


<defn>.....</defn>

</metric>

<metric>

<name>GSM</name>

<defn>

</defn>

</metric>

<select>

........


........

</select>

........


<set>


<elements>



<elements>



</elements>

<elements>



</elements>

<elements>



</elements>

</set>


<val>90</val>

<val>180</val>

<val>365</val>

</set>


<and> <xprod> <in>




12 different columns will be generated from this

single expression

3 Steps

4 segments


<set>


<elements>



<elements>



</elements>

<elements>



</elements>

<elements>



</elements>

</set>


<val>90</val>

<val>180</val>

<val>365</val>

</set>


<and> <xprod> <in>




12 different columns will be generated from this

single expression

3 Steps

4 segments ......

......

......













......

Software

H2O World - PAAS: Predictive Analytics offered as a Service - Prateem Mandal