Optimizing Your Analytic s L ife Cyc le with SAS & T e r - - PowerPoint PPT Presentation

▶
optimizing your analytic s l ife cyc le with sas t e r
SMART_READER_LITE
LIVE PREVIEW

Optimizing Your Analytic s L ife Cyc le with SAS & T e r - - PowerPoint PPT Presentation

Aug 16, 2023 365 likes •629 views

Optimizing Your Analytic s L ife Cyc le with SAS & T e r adata Paul Se gal - T e r adata June 2017 Ag e nda T he Ana lytic L ife Cyc le Co mmo n Pro b le ms SAS & T e ra da ta so lutio ns 2 Ana lytic

slide-1
SLIDE 1

Optimizing Your Analytic s L ife Cyc le with SAS & T e r adata

Paul Se gal - T e r adata

June 2017

slide-2
SLIDE 2

2

  • T

he Ana lytic L ife Cyc le

  • Co mmo n Pro b le ms
  • SAS & T

e ra da ta so lutio ns

  • Ag e nda
slide-3
SLIDE 3

3

Ana lytic a l L ife Cyc le

3

Preparation Prepare Data for Analytics Exploration Explore All Your Data Deployment Deliver Results to Business Development Build Analytic Models

slide-4
SLIDE 4

4

Ana lytic a l L ife Cyc le

T E XT

PRE PARAT ION DE VE L OPME NT DE PL OYME NT E XPL ORAT IO N

  • wha t the d a ta lo o ks like
  • wha t va ria b le s a re in the d a ta se t
  • whe the r the re a re a ny missing
  • b se rva tio ns
  • ho w a re the d a ta re la te d
  • wha t a re so me o f the d a ta pa tte rns
  • c o mb ining da ta fro m nume ro us so urc e s
  • ha ndling inc o nsiste nt o r no n-sta nda rdize d

da ta

  • c le a ning dirty da ta
  • inte g ra ting da ta tha t wa s ma nua lly e nte re d
  • de a ling with se mi-struc ture d a nd struc ture d

da ta

  • c usto me r re te ntio n
  • c usto me r a ttritio n/ c hurn
  • ma rke ting re spo nse
  • c o nsume r lo ya lty a nd o ffe rs
  • fra ud d e te c tio n
  • c re d it sc o ring
  • risk ma na g e me nt
  • the pro b a b ility o f re spo nd ing to a pa rtic ula r pro mo tio na l
  • ffe r
  • the risk o f a n a pplic a nt d e fa ulting o n a lo a n
  • the pro pe nsity to pa y o ff a d e b t
  • the like liho o d a c usto me r le a ve / c hurn
  • the pro b a b ility to b uy a pro d uc t

Stage 2 Stage 1 Stage 3 Stage 4

slide-5
SLIDE 5

5

Co mmo n Pro b le ms

5

slide-6
SLIDE 6

6

T ypic a l Custo me r Cha lle ng e s

  • “ My a na lytic a l pro c e ss runs to o slo wly* ”
  • “ We spe nd to o muc h time mo ving da ta a ro und b e twe e n syste ms ”
  • “ I

wa nt to ma ke mo re / b e tte r use o f my E DW/ da ta pla tfo rm”

  • “ I

t ta ke s fo re ve r to e xtra c t a nd sc o re the da ta ”

  • “ T

he re is to o muc h da ta fo r us to a na lyse ”

  • “ We c a n’ t b uy ne w ha rdwa re ”
  • “T

he q ua lity o f o ur a na lytic a l mo de ls is lo we r b e c a use we sa mple – I wo rry we a re missing va lua b le se g me nts”

* sc o ring / a na lysis / da ta q ua lity / da ta tra nsfo rmatio n

slide-7
SLIDE 7

7 LINE O F BUSINESS

ADW

EDW

PRO G RAM MANAG ER FINANC E SUPPLY C HAIN I.T . HR

T he Ana lytic Da ta Wa re ho use

slide-8
SLIDE 8

8

Da ta Ma na g e me nt: T he c rux o f the issue fa c ing yo ur a na lysts BUSI NE SS PROBL E M BUSI NE SS DE CI SI ON

20%

80%

Pre pa ring to so lve the pro b le m So lving the pro b le m

slide-9
SLIDE 9

9

Da ta Ma na g e me nt: SAS & T e ra da ta wo rking to c ha ng e the E q ua tio n BUSI NE SS PROBL E M BUSI NE SS DE CI SI ON

20%

80%

Pre pa ring to so lve the pro b le m So lving the pro b le m

slide-10
SLIDE 10

10

Ba rrie rs to the Ado ptio n o f Ana lytic s

Sc a r c ity of a na lytic a l skills

T he ne e d to g ro w analytic al tale nt fro m within

Disjointe d, ine ffic ie nt wor kflow

Ho w c an yo u fail fast & le arn to re fine q uic kly T

  • ols that ar

e n’t r ight for the job L e arning c urve to c re ate , share and c o llab o rate

slide-11
SLIDE 11

11

SAS & T e r adata Solutions

1 1

slide-12
SLIDE 12

12

Ana lytic a l L ife Cyc le

Deployment Preparation

a

Exploration Development

  • ACCESS to

Teradata

  • Code

Accelerator

  • Data Quality

Accelerator

  • Data Set

Builder for SAS

CUSTOMER CUSTOMER NUMBER CUSTOMER NAME CUSTOMER CI TY CUSTOMER POST CUSTOMER ST CUSTOMER ADDR CUSTOMER PHONE CUSTOMER FAX ORDER ORDER NUMBER ORDER D A T E STATUS ORDER I TEM BACKORDERED QUANTI TY I TEM QUANTI TY DESCRI PTI ON ORDER I TEM SHI PPED QUANTI TY SHI P DATE
  • Analytics

Accelerator for Teradata

  • SAS High-

Performance Analytics Products

  • TD Appliance

for SAS

  • Visual

Analytics & Visual Statistics

  • Teradata

Appliance for SAS

  • SAS Scoring

Accelerator

  • SAS Model

Manager

  • Teradata

Appliance for SAS

slide-13
SLIDE 13

13

DEPLOYMENT FLEXIBILITY: DESKTOP - SERVER - IN-DATABASE - IN-MEMORY

  • CLOUD

ARCHITECTURE FLEXIBILITY: SMP - MPP - HADOOP - GRID - ESP

Info rma tio n Ma na g e me nt Da ta Mining / Ano ma ly De te c tio n T e xt Ana lytic s Pre dic tive Ana lytic s Hig h Pe rfo rma nc e Ana lytic s F ra ud & Risk De te c tio n Re po rting & Visua liza tio n

I nte g ra te d E nd-to -E nd F

  • unda tio n

SAS Ana lytic s in T e ra da ta

slide-14
SLIDE 14

14

I n-Da ta b a se F unc tio na lity

  • PROC APPE

ND

  • PROC CONT

E NT S

  • PROC COPY
  • PROC DAT

ASE T S

  • PROC DE

L E T E

  • PROC F

ORMAT

  • PROC F

RE Q

  • PROC ME

ANS

  • PROC PRINT
  • PROC RANK
  • PROC RE

PORT

  • PROC SORT
  • PROC SQL
  • PROC SUMMARY
  • PROC T

ABUL AT E

Statistic al Analysis Pr

  • c e dur

e s:

SAS Enterprise Miner

  • PROC CANCORR
  • PROC CORR
  • PROC F

ACT OR

  • PROC PRINCOMP
  • PROC RE

G

  • PROC SCORE
  • PROC T

IME SE RI E S

  • PROC VARCL

US

  • PROC DMDB
  • PROC DMINE
  • PROC DMRE

G (L

  • g istic Re g re ssio n)
  • Also no de s fo r Input, Sa mple , Pa rtitio n, F

ilte r, Me rg e , E xpa nd

SAS Ana lytic s Ac c e le ra tor for T e ra da ta

  • PROC SCORE

wo rks with c o e ffic ie nts fro m:

  • PROC ACE

CL US

  • PROC CAL

IS

  • PROC CANDISC
  • PROC DISCRI

M

  • PROC F

ACT OR

  • PROC PRINCOMP
  • PROC T

CAL IS

  • PROC VARCL

US

  • PROC ORT

HORE G

  • PROC QUANT

RE G

  • PROC RE

G

  • PROC ROBUST

RE G

  • Ma tc h c o de
  • Pa rsing / Ca sing
  • Ge nde r/ Pa tte rn/ Ide ntific atio n

a na lysis

  • Sta nda rdiza tio n

SAS/ Ac c e ss to T e ra da ta :

  • PROC DS2

SAS Code Ac c e le r ator for T e r adata SAS Sc or ing Ac c e le r ator for T e r adata

  • E

M/ ST AT * Mo de ls

DQ Ac c e le ra tor for T e ra da ta

slide-15
SLIDE 15

15

I n-Da ta b a se E xa mple : Da ta Qua lity

  • SAS Da ta Qua lity func tio ns po rte d to
  • pe ra te in-datab ase
  • I

nvo ke d a s SQL Sto re d Pro c e dure s

  • Pro c e ssing le ve ra g e s pa ra lle lism o f

unde rlying RDBMS

  • Sig nific a nt pe rfo rma nc e / thro ug hput

b e ne fits

  • Suppo rte d func tio ns:
  • Ma tc hc o de g e ne ra tio n
  • Pa rsing
  • Sta nda rdiza tio n
  • Ca sing
  • Pa tte rn a na lysis
  • I

de ntific a tio n a na lysis

  • Ge nde r a na lysis
slide-16
SLIDE 16

16

E xplo ra tio n a nd mo de ling – wha t do e s it b ring ?

Influe nc e Re la tionships Contributions Da ta drive n e xplora tion E limina ting g ue sswork with pre dic tive a na lytic s

Inc r e ase d unde r standing

slide-17
SLIDE 17

17

SAS Visua l Ana lytic s & Visua l Sta tistic s

SAS Visua l Ana lytic s

  • Da ta e xplo ra tio n a nd d isc o ve ry
  • Distrib utio n a nd summa ry sta tistic s
  • Po st-mo d e l a na lysis a nd re po rting

SAS Visua l Sta tistic s

  • Build pre d ic tio n a nd c la ssific a tio n

mo d e ls

  • Re fine c a nd id a te mo d e ls
  • Co mpa re mo d e ls a nd g e ne ra te sc o re

c o d e

slide-18
SLIDE 18

18

  • Ana lyze 100% o f da ta
  • Mo re / Ne w va ria b le s
  • Mo re mo de l ite ra tio ns
  • Ma na g e c o mple x mo de ls
  • Mo re mo de ls (pe r do ma in a re a )
  • Mo re q ue stio ns/ ide a s/ sc e na rio s to

e va lua te

  • Multiple de plo yme nt o ptio ns: b a tc h,

re a l-time

  • Co ntinuo usly mo nito r mo de l

e ffe c tive ne ss a nd re tra in

SAS Hig h-Pe rfo rma nc e Ana lytic s

slide-19
SLIDE 19

19

SAS Hig h-Pe rfo rma nc e Ana lytic s Pro c e dure s

SAS High- Performance Statistics SAS High- Performance Econometrics SAS High- Performance Optimization SAS High- Performance Data Mining SAS High- Performance Text Mining SAS High- Performance Forecasting HPCANDISC HPFMM HPPLS HPPRINCOMP HPQUANTSELECT HPLOGISTIC HPREG HPLMIXED HPNLIN HPSPLIT HPGENSELECT HPCDM HPCOPULA HPPSNEL HPCOUNTREG HPSEVERITY HPQLIM OPTLSO Select features in OPTGRAPH OPTMILP OPTLP OPTMODEL HPBNET HPCLUS HPSVM HPTSDR HPREDUCE HPNEURAL HPFOREST HP4SCORE HPDECIDE HPTMINE HPTMSCORE HPFORECAST The above offers contain these standard PROCS: HPDS2, HPDMDB, HPSAMPLE, HPSUMMARY, HPIMPUTE, HPBIN, HPCORR

slide-20
SLIDE 20

20

HPA E xa mple

SAS Ana lyst’ s De skto p

T ra ditio na l SAS Se rve r SAS HPA E nviro nme nt

slide-21
SLIDE 21

21

Pla tfo rms fo r Optima l SAS Pe rfo rma nc e

Suppo rts SAS in-me mo ry a na lytic s to o ls use d to visua lize da ta a nd b uild da ta mo de ls, g iving the m dire c t a c c e ss to da ta within the Ac tive Da ta Wa re ho use E na b le s SAS in- da ta b a se a na lytic s to c le a n a nd pre pa re da ta a s we ll a s de plo y a nd sc o re mo de ls witho ut ha ving to mo ve the da ta . Pro vide s a c o st e ffe c tive , pre c o nfig ure d da ta sto ra g e a nd sta g ing a re a tha t ma ke s da ta a va ila b le fo r SAS a na lytic s

Teradata Active Data Warehouses Teradata Appliance for SAS Teradata Appliance for Hadoop

slide-22
SLIDE 22

22

A F ully Co nta ine d SAS E c o syste m in One Bo x

Data Persistent Teradata Appliance for SAS Teradata 2800 Appliance with SAS Analytics

A fully c ontain SAS Analytic s E c osyste m in a single box fr

  • m

T e r adata that inte gr ate s the SAS se r ve r dir e c tly into the c abine t with your data

SAS Managed Server from Teradata

T E RADAT A

slide-23
SLIDE 23

23

Custo me r Suc c e ss Sto ry

  • Pro je c ts invo lving hig h-

e nd a na lytic s we re pla c ing mo re a nd mo re de ma nd o n I T a nd Busine ss Ana lytic s te a ms

  • Ne e de d to stre a mline

the a na lytic s wo rkflo w

  • Ne e de d a so lutio n tha t

pro vide d sc a la b ility a nd da ta c o nsiste nc y

  • Pro c e ss c o uld no t

suppo rt a dditio na l a na lytic s re q ue sts witho ut a dding he a dc o unt

  • Re pla c e d de skto p to o ls

with SAS se rve r b a se d HPA to o ls suc h a s E nte rprise Mine r, Sc o ring Ac c e le ra to r, Mo de l Ma na g e r, VA & Da ta Mining

  • Adde d T

e ra da ta Applia nc e fo r SAS fo r pro duc tio n a nd de ve lo pme nt o f da ta mo de ls

  • E

xpa nde d E DW

  • Adde d Da ta L

a b s E nviro nme nt to

  • I

mpro ve d the spe e d a nd pe rfo rma nc e o f a na lytic s

  • Stre a mline d da ta

pre pa ra tio n, e va lua tio n a nd te sting

  • Adde d a dditio na l

a na lytic s c a pa c ity witho ut re q uiring the a dditio n o f ne w he a dc o unt

  • F

re e d up I T time use d fo r da ta c o lle c tio n, lo a ding a nd pre p

L e ve ra g ing SAS a nd T e ra da ta fo r a dva nc e d a na lytic s to a na lyze c usto me r da ta a nd lo ya lty pro g ra ms with in-da ta b a se a nd in-me mo ry te c hno lo g ie s

I ssue s So lutio ns I mpa c t

L ar ge US Re taile r

slide-24
SLIDE 24

24

  • Minimize the ne e d to mo ve the da ta
  • F

a ste r mo de ling time s (mo nths/ we e ks to ho urs/ minute s)

  • I

mpro ve da ta q ua lity, a va ila b ility a nd c o nsiste nc y

  • Wo rk with e ntire da ta se ts, inc luding e na b ling a n

e nd-to -e nd vie w o f da ta fro m a c ro ss the e nte rprise

  • F

re e up sta ff to fo c us mo re time o n va lue -a dding a c tivitie s

Summa ry

slide-25
SLIDE 25

25

  • Da ta mo de ling de ve lo pme nt with SAS

E nte rprise Mine r a nd T e ra da ta

  • Hig h Pe rfo rma nc e Ana lytic s with T

e ra da ta

  • Sc o ring da ta in T

e ra da ta with SAS Sc o ring Ac c e le ra to r

  • De mo – Mo de ling a nd De plo yme nt