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Powering up Analytics with Big data -the SAS Way!. -Priya Sarathy, ph.d Analytic Sales Consultant, SAS. Salute to the world run by Statisticians. Play. Agenda. High Performance Analytics (HPA) Meeting Challenges The What? Understanding the Analytic paradigm Shift

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powering up analytics with big data the sas way
Powering up Analytics with Big data -the SAS Way!

-Priya Sarathy, ph.d

Analytic Sales Consultant, SAS

slide3
Agenda

High Performance Analytics (HPA)

  • Meeting Challenges
  • The What?
  • Understanding the Analytic paradigm Shift
  • High Performance Analytics – the SAS way
  • What is the business value add
high performance analytics
High Performance Analytics

What is HPA delivering

What is HPA about?

  • Evolving business needs

Why does business need it?

  • Leveraging information to compete in the market
  • Raise revenue/ profits
  • Reduce costs and inefficiencies
high performance analytics grew from the need for big data analytics

Big Data Analytics

  • Big Analytics
High performance Analytics grew from the need for big data Analytics!

Proactive

Analytic Capabilities

BI

Big Data BI

Reactive

Big

Large

Data Size

high performance analytics1
High performance analytics

Hpa is impacting business performance in many areas

high performance analytics2
High performance analytics

What Conversations are you involved in?

what do others think
What do others think?

Data measurement is the modern equivalent of the microscope*

At the World Economic Forum last month in Davos, Switzerland, Big Data was a marquee topic. A report by the forum, “Big Data, Big Impact,” declared data a new class of economic asset, like currency or gold.

28 year Asst. professor at Stanford combined math with political science in his undergraduate and graduate studies, seeing “an opportunity because the discipline is becoming increasingly data-intensive.” His research involves the computer-automated analysis of blog postings, Congressional speeches and press releases, and news articles, looking for insights into how political ideas spread.

It’s not just more streams of data, but entirely new ones- countless digital sensors worldwide in industrial equipment, automobiles, electrical meters and shipping crates- measure and communicate location, movement, vibration, temperature, humidity, even chemical changes in the air..

* Quote from Professor Brynjolfsson

The Age of Big Data, By STEVE LOHR, NYT

slide11
The new Normal – what is HPA doing to Analytics?

Analyze 100% of data

More/New variables

More model iterations

Manage complex models

More models (per domain area)

More questions/ideas/scenarios to evaluate

Multiple deployment options: batch, real-time

Continuously monitor model effectiveness and retrain

The Things you can Think!

high performance analytics3
High Performance Analytics

HPA combines the three pillars to deliver results

Data: Leveraging technology to collect, access and manage data

Analytics: Adapting to new technology, In-memory, Grid, In-database

Platform: Positioning analytics within industry leaders technology solutions

high performance analytics4
High Performance Analytics

advanced analytics and fast computing capabilities are brought together with SAS HPA

In a recent National Postinterview with Jim Goodnight, the SAS CEO explains it like this:

There's a lot of business processes that will be changing because of the speed at which we can do analytics; using a thousand processes in parallel to do these computations can make it possible to do huge problems that we would never have been able to do before because it would take too long on a single processor.

A big part of how HPA gets its speed: it breaks larger problems down into smaller pieces.

high performance analytics5
High Performance analytics

From Sampling to Populations analysis

50 Attributes to 500+ Attributes

Reduce run times 18 Hrs - 30 minutes

Build more complex models

3 month Lagged modeling to Real time updates

Structured data to combining unstructured data

Shortening model lifecycle

More frequent updates, model iterations

real time scoring impacting business bottom-line

HPA Helps remove limitations

You will have more time to think!

model lifecycle
Model lifecycle

How much time do you spend on your models?

Where would you like to spend more time?

Data Analysis

45%

Monitoring & Results Reporting

15%

Model Build

30%

Validation & Implementation

10%

responsibilities of an statistical analyst
Responsibilities of an Statistical Analyst

Model building paradigm Shift

Extract, Transform, Load data

Data massaging/ mining

Aggregating, normalizing data

Identifying Analytic approach

Building Samples

Building Models

Creating Scoring Code

Validation Reports/ model documentation

Implementation for Production

Results monitoring

Update, refresh, or rebuild model

IT – shifting responsibilities to

EDW/ DW

Data Quality

Data integration

ODS

Production implementation

Analyst – building models

Access to more and better data

Need for documentation and transparency

Greater number of business solutions

Changing market and data dynamics impacting frequency of build and update

model lifecycle1
Model lifecycle

Changing roles and responsibilities

New technology, new tools

New business processes

New competitive demands

Data Analysis

25%

Monitoring & Results Reporting

5%

Model Build

60%

Validation & Implementation

10%

the farfalle model
The Farfalle Model

The basic structure of analytic function

Analytics as a commodity

Source: IDC, 2012

  • 70% of the effort in analytics is typically on the information management side of the model.
  • Analytical teams in the middle are small but crucial for translating the data assets into actionable insights.
  • The organization change side highlights the attributes of behavior changes needed by business users.
slide20

Working with a Tsunami of data

VOLUME

VARIETY

VELOCITY

DATA SIZE

VALUE

TODAY

THE FUTURE

sas high performance analytics
SAS® HIGH-PERFORMANCE ANALYTICS

Embracing new technology, building new strengths

Visual Analytics

physical layout
Physical Layout

Scalable analytic Capability

COMPUTING FRAME

CLIENT FRAME

DATA FRAME

MID-TIER

Node 1

SAS Analytic

& Scoring

Accelerators

RDMBS

Node 2

Shared / Clustered File

SAS Metadata Servers

[Controller Node n cores]

SAS Analytic

& Scoring

Accelerators

Node n

HADOOP

high performance analytics6
High Performance Analytics

Changing the way Analytics is done bottoms up

  • HPLOGISTIC
  • HPREG
  • HPLMIXED
  • HPFOREST
  • HPNEURAL
  • HPREDUCE
  • HPNLIN
  • SUMMARY/MEANS
  • FREQ
  • RANK
  • DS2
  • SORT
sas high performance analytics server
SAS® High-Performance Analytics Server

Areas of Model Development that benefit

  • Predictive Analytics & Data Mining
  • Binary target & continuous no. predictions
  • Linear & Non-Linear modeling
  • Complex relationships
  • Tree-based Classification
  • Text Mining
  • Parsing large-scale text collections
  • Extract entities
  • Auto. stemming & synonym detection
  • Topic discovery
  • Optimization*
  • Local search optimization
  • Large-scale linear & mixed integer problems
  • Econometrics Time Series
  • Probability of an event(s)
  • Severity of random event(s)

*Currently only available for Teradata and EMC Greenplum

financial services
Financial services

Customer acquisition use case

Current Process

High-Performance Process

MODEL

DEVELOPMENT

MODEL

DEPLOYMENT

DATA

EXPLORATION

One algorithm (Neural Network)

Multiple algorithms (e.g. Forest, Logistic Reg., etc.)

1 model per day

1 model per 30 minutes

5 hours to process model

3 minutes to process model

84

SECONDS

Model lift of 1.6%

Model lift of 2.5%

slide28

Think left and think right and think low and think high. Oh, the thinks you can think up if only you try!Oh the things you can find, if you don't stay behind! Dr. Seuss(On Beyond Zebra!, 1955)

sas high performance analytics server1
SAS® High-Performance Analytics Server

Key differentiators

Only in-memory offering in the market delivering high-end analytics, including text mining and optimization

Addresses the entire model development and deployment lifecycle

36 years of proven technology...faster. Opens up vast array of possibilities to get value from big data

slide31
Top five ways high-performance analytics will transform marketing

Faster, more sophisticated, effective segmentation

  • segmentation tests can be run against the entire populations in order to determine the best campaign interaction methods

Real-time, relevant next-best customer actions or offers

  • This results in a more relevant offer or customer interaction surfacing at the “point of need” in real-time

Instant deployment and management of marketing models that give you a sustainable advantage

  • companies to quickly and efficiently update their numerous models without submitting a slow overnight batch update process.

1:1 real-time experiences to bolster brand connections

  • The outcome is more precise, real-time interactions with consumers at the “point of need.”

Optimized marketing for broader business impact

  • Now businesses can not only determine the customer and financial impacts of their campaigns faster but also adapt instantaneously to market, competitive and customer changes.
united healthcare group
Healthcare payer

BUSINESS ISSUE

Electronic medical records (EMRs) driving a data explosion

Utilize all of the unstructured text (records, case notes, emails, transcripts, etc.)

How to improve quality and cost of care? “Create Healthier Lives”

SOLUTION

SAS® High-Performance Analytics Server including HP Text Mining

Greenplum Data Computing Appliance

RESULTS

Reduce model processing time from four hours to 10 seconds.

Reduce misclassification rates from 30% to 10%

Historical models improved with more than 10% lift

I can now tell that a prescription will harm a patient before you write it…

I can tell that a customer is dissatisfied before you lose him or her...

I can now determine that a claim is fraudulent before you pay it…

“ SAS is helping make our member services the best in the industry, In less than one hour, we can load a huge table (169 million row dataset), find the best variables, compare different models and pick the best model. I would not attempt to model a dataset this large without SAS HPA Server.”

Mark Pitts

Director of Data Science, Solutions and Strategy

united healthcare group
sas high performance
SAS High-Performance

Leveraging Database Appliance for HPA

Request is

sent to the

root node

inside the

appliance

Root Node

(Teradata Managed Server)

Worker Node 1

Worker Node 2

Worker Node N

sas high performance1
SAS High-Performance

Analytical Computation and data request sent to the worker nodes

Root Node

Worker Node 1

Worker Node 2

Worker Node N

sas high performance2
SAS High-Performance

Data request sent to the database. data slice moved into memory

Root Node

sas high performance3
SAS High-Performance

Analytic Processing with internode communication

Root Node

sas high performance4
SAS High-Performance

Worker node returned to the root node. Job is

complete.

Root Node