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SAS FOR BUSINESS ANALYTICS

PAST, PRESENT AND FUTURE

Jos van der Velden <[email protected]>Education & Academic Program – SAS Iberia


AGENDA BUSINESS ANALYTICS: MAKING SENSE OF DATA

The SAS Story

The SAS Platform

SAS Use Cases

SAS for IoT

The Future

SAS Academy

for Data Science


THE SAS STORY


THE SAS PLATFORM

A MULTI-TIER ARCHITECTURE


SAS MULTI-TIER PLATFORM ARCHITECTURE

Data Sources SAS Servers Middle Tier Clients


SAS TECHNOLOGIES AND ANALYTICS


SAS USE CASES

APPLYING TRADITIONAL ANALYTICS


WILDTRACK SAVES ENDANGERED SPECIES


SAS FRAUD FRAMEWORK


INSURANCE FRAUD ANALYSIS


PRESENT

MACHINE LEARNING


Automate

• Provide automation to the model building

process by minimizing human intervention

Customize

• Build powerful models using SAS’s state-of-

the-art algorithms in conjunction with open

source tools

Speed

• Fast response time for sophisticated analytics

applied to data of any size or complexity

SAS ANALYTICS IN ACTION

Machine Learning


Machine

Learning


WHAT IS MACHINE LEARNING?

Machine learning is a branch of

artificial intelligence that

automates the building of

systems that learn iteratively from

data, identify patterns, and predict

future results – with minimal

human intervention. It shares

many approaches with other

related field, but it focuses on

predictive accuracy rather than

interpretability of the model

FUN FACT: More than 30 years ago, SAS CEO, Jim Goodnight wrote a procedure for "k-nearest neighbor

discriminant analysis," which is a machine learning method! And growing since….

SAS Data Mining Primer course 1998

Machine

Learning


MACHINE LEARNING : WHY IS IT SO IMPORTANT NOW?

Data Computing

Power

Algorithms


APPLICATIONS OF MACHINE LEARNING

Predictive Asset

Maintenance

FraudCredit Scoring

Next Best Offers Customer Segmentation

Targeted Acquisition /

Retention / AttritionReal-time Ad

placements

Natural Language

Processing

Network Intrusion

Detection

Online

Recommendations

Customer Lifetime

Value


MACHINE LEARNING: USERS

BUSINESS USERS

DATA SCIENTISTS

STATISTICIANS

PRIMARY AUDIENCE

IT

SECONDARY AUDIENCE

IT needing to “scale up” is

dependent on the

Business’s desire to do so.

IT should recognize value

of tested, business ready

decision flow


BUSINESS CHALLENGES

Critical decision making

information gets lost in big

data

Customers and markets are more

demanding than ever requiring quicker

and more accurate responses

Analytical talent for data driven

decision making can be hard to find


SAS FOR BIG DATA ANALYTICS

SAS HADOOP ECOSYSTEM


SAS HADOOP ECOSYSTEM


SAS ANALYTICS IN ACTION

THE ANALYTICS

FAST TRACK™

FOR SAS®

Wide range of use cases

• Tailored to customers’ business issues

Rapid deployment

• See value in days, not months

State of the art platform

• Accelerate the analytics process

Analytics Fast Track™ for SAS®


SAS FOR THE INTERNET-OF-THINGS

EVEN MORE CHALLENGES AND OPPORTUNITIES


nternet

OF

hings

I

T

Healthcare

Connected Car/

Transportation

Communications

Energy

Connected CustomerSmart Cities and Homes

Surveillance

Building

Management

Agriculture

Retail

ManufacturingInsurance


ANALYTICAL LIFE-CYCLE WITH IOT


INTERNET OF

THINGSCHALLENGES

Challenges

• Operationalize

• Monitor

• Data

• Breadth and Depth

• Art and Science

• Volume

• Variety

• VelocityBig Data

Analytics

Act


INTERNET OF

THINGSTRADITIONAL ANALYTICS LIFECYCLE

DeployETL

Data Data Storage

f

Access – Store - Analyze

Alerts / Reports


Deploy

INTERNET OF

THINGS

IOT ANALYTICS LIFECYCLESENSE – UNDERSTAND - ACT

ETL

Data Data Storage

Alerts / Reports/ Decisioning

Deplo

y

f

IoT Data Intelligent Filter / Transform

Streaming Model Execution


THE CONNECTED VEHICLE


Connected Service

Improving service operations through

predictive maintenance. SAS IoT Analytics

provides manufacturers with new insights that

proactively identify equipment issues,

positively impacting customer satisfaction

and service profitability.

SAS IoT Analytics quickly detects and alerts of leaks and abnormal water

usage, providing the city and their citizens valuable information that help them use water more wisely.

Connected Cities Connected Energy

Improving profitability and customer service

by leveraging data from smart meters, applying

SAS IoT Analytics, to more accurately predict

both short and long term demand.

Global Healthcare

ManufacturerAustralian Utility

Connected Factory

Identifies hidden patterns that predict

failures improving production yield and

product quality. SAS IoT Analytics leverages

equipment sensor and tag data to develop and

deploy early warning models.

INTELLIGENCE FOR THE CONNECTED WORLD


Connected CustomerConnected Car

Predict issues in the fleet before failures occur and

provide new value added services. SAS IoT

Analytics uses data vehicle sensors and

customer information to develop and deploy models that provide

proactive information leading to better customer service.

Connected Mobility

INTELLIGENCE FOR THE CONNECTED WORLD

Connected Health

Ensure uninterrupted service and passenger

safety. SAS IoT Analytics leverages data from

tracks and vehicles to predict potential issues

that compromise performance and safety,

and optimize maintenance schedules leading to safer, more

reliable service.

Improve patient care and drive better patient

outcomes. SAS IoTAnalytics allows health care organizations to leverage electronic

medical recorders with health sensors to

establish optimal care and monitor conditions

in real – time to minimize risks.

Provide your customers with the right content and offers in real time.

SAS IoT Analytics leverages data from set box devices to predict

customer preferences, in real time. The result is timely suggestions and

offers customers are more likely to accept.

Global

Telecommunications

Company


THE FUTURE

COGNITIVE COMPUTING, DEEP LEARNING AND LIFELONG LEARNING


Infinite Volume and Variety of Data

Disruptive Technology

New Problem-solving Mindset

UnprecedentedProcessing Power

THE FUTURE


DEEP LEARNING ENABLED BY SAS VIYA

• Cognitive computing involves self-learning systems

that simulate human thought processes in a

computerized model.

• Foundations of Cognitive Computing are

• Natural Language Processing

• Deep Learning

• Intelligence automation

& COGNITIVE

COMPUTING


SAS®

VIYA™

OVERVIEW

Customer ready presentation


““In the new world, it is not the big fish

which eats the small fish, it’s the fast

fish which eats the slow fish.”Klaus Schwab

Founder and Executive Chairman

World Economic Forum


• Encourage, foster, and capture

innovation

• Turn innovation into disruption

• Create repeatable, auditable

processes

• Create new business and

engagement models

• Anticipate and address

customer needs

• Remain vigilant: efficient,

compliant, secure

Established OrganizationsInnovators & DisruptorsOutlive the hype and establish permanence Fuel innovation, maintain success, and avoid risk


OUR R&D JOURNEY

SAS®

High-Performance

Architecture

2010

SAS®

In-Memory

Analytics Server

2011

SAS®

3rd Generation

Massively Parallel

Architecture

2013Development

Timelines


SAS 9.4 MULTI-VENDOR ARCHITECTURE

MVS

Windows

AIXHP-UX

Solaris

SunOS Linux

Tru64

IRIXOS/2


MVS

Windows

AIXHP-UX

Solaris

SunOS Linux

Tru64

IRIXOS/2 Google

Cloud

Platform


SAS®

Viya™

CAPABILITIES AND BENEFITS

• Extend applications with

Public REST APIs

• Familiar languages

(SAS, Python, Lua,

Java)

Self-service

Innovative algorithms

Portable analytic assets

• Common code, CLI framework

• Complete analytics

lifecycle

• Ease of management

Elastic scalability

Per use /

consumption-based pricing

Architecture flexibility


Pa

ralle

l &

Se

ria

l, P

ub

/ S

ub

,

Web S

erv

ice

s, M

Qs

Source-basedEngines

Microservices

UAA

Query

Gen

Folders

CAS

Mgmt

Data

Source

Mgmt

Analytics

GUIs

etc.…

BI

GUIs

Env

Mgr

Model

Mgmt

Log

Audit

UAAUAA

Data

Mgmt

GUIs

In-Memory Engine

In-Cloud

In-Database

In-Hadoop

In-Stream

Solutions

APIs

Infrastructures

Platforms

SAS®

Viya™

CONCEPTUAL ARCHITECTURE

Analytics

Data ManagementFraud and Security Intelligence

Business VisualizationRisk Management

!

Customer Intelligence

Cloud Analytics Services (CAS)


Expand analytic

toolkit. Code in

the language of

your choice.

Scale methods

without

redefining code.

Easily wrangle

data.

Interactively

interrogate.

Discover insights

through visual

interface.

Include SAS

analytics in

applications.

Documented

REST APIs.

Centralized

management of

analytic assets.

One governed

environment.

Multi-cloud for

flexibility.

Failover

protection.

Guided

workflows.

Visual interface

accelerate

investigations.

Analytic

intelligence

built-in.

Consistent

answers. Use

current

hardware.

Extend analytics

use with existing

skills.


SAS®

Viya™

MARKET DIFFERENTIATION

Single environment, common code base that is…• Executable anywhere (in-Memory, in-Database, in-

Hadoop, in-Cloud, in-Stream, in-Device)

• Portable to any IT environment (desktop, server, grid,

cluster, or cloud)

• Accessible from third party applications

• Available in any public / private cloud

• Capable of management and inventory of all analytics

assets

• Infused with sophisticated and native search that does

not require pre-defined schemas in applications

Support for the Analytics Lifecycle• Data Management

• Visual Data Exploration

• Interactive Discovery

• Advanced Analytics

• Model Versioning & Inventory

• Decision Management

• Reporting

• Dashboards


SAS ACADEMY FOR DATA SCIENCE


SKILLS REQUIRED FOR THE DATA SCIENTIST


SAS ACADEMY FOR

DATA SCIENCE

KEY COMPETENCIES OF AN

ANALYTICS WORKFORCE

Big Data

Management

Data

Visualization

Statistics and

Machine

Learning

Communication

Deployment,

and Automation

SAS Certified Big Data

Professional Level 1SAS Certified Advanced Analytics

Professional Level 2

SAS Certified Data Scientist

(level 1 and 2)


OUR FUTURE

Wharton Folly: A Playground of Lifelong LearningIllustration by Michael Witte

Jos van der Velden - ISCTEhome.iscte-iul.pt/~earc/Seminars/SAS4BusinessAnalytics.pdf ·...

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