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#AnalyticsXC o p y r ig ht © 201 6, SAS In st i tute In c. A l l r ig hts r ese rve d.

The Value of Moving Streaming Analytics Outside the Data Center

Mark LochbihlerDirector, Partner EngineeringHortonworks

1 © Hortonworks Inc. 2011 – 2016. All Rights Reserved

Disclaimer

This document may contain product features and technology directions that are under development, may be under development in the future or may ultimately not be developed.

Project capabilities are based on information that is publicly available within the Apache Software Foundation project websites ("Apache"). Progress of the project capabilities can be tracked from inception to release through Apache, however, technical feasibility, market demand, user feedback and the overarching Apache Software Foundation community development process can all effect timing and final delivery.

This document’s description of these features and technology directions does not represent a contractual commitment, promise or obligation from Hortonworks to deliver these features in any generally available product.

Product features and technology directions are subject to change, and must not be included in contracts, purchase orders, or sales agreements of any kind.

Since this document contains an outline of general product development plans, customers should not rely upon it when making purchasing decisions.

2 © Hortonworks Inc. 2011 – 2016. All Rights ReservedPage 2 © Hortonworks Inc. 2011 – 2015. All Rights Reserved

Your Presenter

Mark Lochbihler

Hortonworks Partner Engineering

@MarkLochbihler

“26 years of Experiencein Computer Science, SAS and Data Platforms”


Today’s Agenda September 14th, 2016

• Hortonworks and SAS Partnership• Data Explosion, the Market and Joint Customer Stories

• Hortonworks Connected Data Platforms• Hortonworks Data Platform

• Hortonworks Data Flow

• Hortonworks and SAS Integrations (High Level Overview)

• Focus on SAS ESP Integrations with HDP and HDF• SAS ESP running in HDP

• SAS ESP running with HDF

• Edge Analytics Value Summary


Hortonworks and SAS Partnership


Founded in 2011

Original 24 architects, developers, operators of Hadoop from Yahoo!

800+E M P L O Y E E S

1500+E C O S Y S T E M P A R T N E R S

• 800+ customers (as of Jan 1st, 2016)

• Publicly traded on NASDAQ: HDP

• The Leader in Connected Data Platforms

Data in Motion - Hortonworks Data Flow

Data At Rest - Hortonworks Data Platform

Powering Modern Data Applications

• Leader in open-source community, focused on innovation to meet enterprise needs

• Unrivaled Hadoop support subscriptions


SAS + Hortonworks Global Alliance

Strategic alliance established October 2013

Dedicated Alliance Management

Tier-1 Hadoop Distribution Vendor for SAS

Joint R&D with YARN integration

Joint Product Roadmap

Both – Founding Members of ODPi and DGI

"The expanded integration of SAS w ith

Hortonw orks Data Platform provides a simple

w ay for customers to broaden their analytic

operations across new data sets that can

drive smarter business decisions."

Shaun Connolly , VP of Corporate Strategy ,

Hortonworks

”Adopting YARN allow s us to use the YARN

infrastructure to set the boundaries for the

processes needed to run SAS HPA products

and SAS LASR Analytic Server based

products. CPU and memory can be capped,

facilitating a better sharing model for the

cluster."

Paul Kent, Vice President, Big Data, SAS


EMBRACE AN OPEN APPROACH

MASTER THE VALUE OF DATA

EVERY BUSINESS IS A DATA BUSINESS


4ZBDATAINTERNET

OF

ANYTHING

44ZBDATA

TOMORROW



Tire Pressure

Server log Mobile

Sensor

Location

Precipitation

Social

Click-stream

Data Powers Highway Safety


Data Powers Better Health

Claims Codes

Server logs Mobile

Sensor

Wearable Devices

EMR Data

Medical Research

Click-stream


Data Powers Digital Security

Emails

MobileSensor

Firewall Log

Virus Definitions

Social

Click-stream

Server Log


Challenge Unable to analyze huge amounts of data to optimize and improve real -time customer insights

Understand audience: Having the largest volume of data sets, audience segments/profile while leading the marketplace in privacy and governance.

Find Audience: Being leaders in identifying and targeting audiences across channels, platforms and devices.

Engage Audience: Driving engagement across platforms and formats.

Measure Audience: Exceeding client expectations with transparent reporting and accurate attribution models.

Solution Integration and analysis of all data collected across the organization

Query ALL data in one location blend of online and offline data, subscription, ecommerce, loyalty programs, etc.

Land massive click stream log fi les, 100+ M records / day, 30 mill ion unique IDs / month

Use 100% of the data for analysis and visualization instead of smaller random samples (over sampling)

Identified and modeled more than 600 relevant web characteristics out of a field of 75,000 with SAS

Customer Insights – SAS leveraging a centralized Big Data Lake

Telco / Media• Large multi-channel

media provider

Why Hortonworks

and SAS?

Customer Insight


Challenge Lack of unified customer record across all channels clouded targeting for marketing campaigns

No “golden record” for analytics on customer buying behavior across all channels

Data repositories on web traffic, POS transactions and in-home services were in silos

Data storage costs were increasing, without a corresponding increase in value

Solution HDP data lake drives golden customer record, targeted marketing, and reduction in data storage expenses

Golden record enables targeted, personalized marketing with higher success rates

Data warehouse offload saved mill ions of dollars in recurring expense

Price optimization versus competitors several mill ions in top-line revenue growth

Unified Customer Record - 360° Customer View - to Improve Sales

Retail

Major home

improvement retailer

Why Hortonworks

and SAS?

Single View


Challenge

Difficulty identifying coding errors among 300K daily claims

Health insurer had goals of marrying electronic health records with claims data

Data analysis is disjointed it difficult to identify coding errors

Undiscovered errors may harm patient health and reduce reimbursement from government programs, costing many mill ions in missed payments

Solution

Using SAS and Hortonworks to improve reimbursement revenue and health outcomes

HDP + SAS: Marrying and analyzing numerous pool of data store in HDP—including gross margins, taxes, customer claims and policy premiums—to determine the company's potential exposure and manage its resources more effectively.

Ability to crunch several terabytes of data, and then revises, recalculates and reports on that data on a weekly basis.

Improve Reimbursement - by Finding Errors in Claims

Insurance

Healthcare

Large US medical

insurer

Why Hortonworks

and SAS?

Data Discovery


Hortonworks Connected Data Platforms


DATA AT RESTDATA IN MOTION

ACTIONABLEINTELLIGENCE

Modern Data Applications

PERISHABLE INSIGHTS

HISTORICAL INSIGHTS

INTERNETOF

ANYTHING

Hortonworks DataFlow

Hortonworks Data Platform

Hortonworks DeliversConnected Data Platforms


The Value of Modern Data AppsCustom or Off the Shelf

Real-Time Cyber Securityprotects systems with superior threat detection

Smart Manufacturingdramatically improves yields by managing more variables in greater detail

Connected, Autonomous Carsdrive themselves and improve road safety

Future Farmingoptimizing soil, seeds and equipment to measured conditions on each square foot

Automatic Recommendation Enginesmatch products to preferences in milliseconds

DATA ATREST

DATA IN MOTION

ACTIONABLEINTELLIGENCE

Modern Data Applications

Hortonworks DataFlow

Hortonworks Data Platform


Hortonworks Data Platform for Data at RestPowered by Open Enterprise Hadoop

Open

Interoperable

Ready

Central


Central Management of Data at RestY A R N

D A T A O P E R A T I N G S Y S T E M

OPERATIONS SECURITY

GOVERNANCE

STOR

AG

ESTO

RA

GE

MachineLearning

Batch

StreamingInteractive

Search

Centralized Platformfor operations, governance and security

Diverse Applicationsrun simultaneously on a single cluster

Maximum Data Ingestincluding existing and new sources, regardless of raw format

Shared Big Data Assetsacross business groups, functionsand users


Secure

Real-time

Adaptive

Integrated

Hortonworks DataFlow for Data in MotionPowered by Apache NiFi


HDF Provides “Data Plan of Control” by Managing IoT Dataflows

Constrained

High-Latency

Localized Context

Hybrid – Cloud/On-Premise

Low -Latency

Global Context

Data source agnostic collection of data across heterogeneous environments


Without HDF

Collecting Source Data is complicated


HDF is a Dataflow Management Platform

With HDF


SAS and Hortonworks Integrations


Hortonworks AND SAS Deliver Advanced Analytics Anywhere!

ESP

ESP

Grid ManagerLASRHP ProceduresCode AcceleratorData Quality AcceleratorEP

Data Management

Data Mining

Data DiscoverAdvanced Analytics


Focus on SAS ESP Integrations

with HDP and HDF


The Value of Event Stream Processing

SAS ESP compliments HDF and HDP by offering“Complex Event Processing” or CEP

Cyber Security - identify a malicious intrusion before or as it occurs

Fraud – analyze streaming transactions to determine which needs immediate attention

Predictive Maintenance – predict outlier conditions from streaming machine and sensor data

Customer Experience and Marketing – use streaming data insights to personalize interactions

Stream Data Management – transform and clean data in motion, storing only what you need


Data Center Approach: SAS ESP processing is co-located within HDP

STOR

AG

E

STO

RA

GE

GROUP 2GROUP 1

GROUP 4GROUP 3

D A T A A T R E S T

INTERNETOF

ANYTHING

In this deployment model - SAS ESP provides “Complex Event Processing” at the point of data being ingested into Hadoop

ESP

HDP


NodeManager NodeManager NodeManager NodeManager

Container 1.1



Container 1.2

Container 1.3

AM 1 Container 3

Container 4

AM3

ESP Job Launcher2

ResourceManager

Scheduler

1) ESP Job Launcher

3a) ESP Server

2) Request ESP: Memory / Core Requirements

3c) ESP Server

3b) ESP Server

AM2

AM4

SAS ESP on HDP is YARN Ready


ESP

ESP

ESP

Remote to Data Center

HDF

HDF

HDF

Extending Streaming Analytics with SAS ESP and HDF

ESP

ESP

ESP ESP

Execute SAS ESP Advanced Analytics as a part of any HDF workflow :

• As data moves between data centers

• As data moves from the Edge or Remote Access Points to a data center

• As data moves from a data centers to the cloud

HDF

Between Data Centers

HDF

HDF

Between Data Centers & Cloud

HDF


SAS ESP can provide “Complex Event Processing” to any HDF workflow

D A T A I N M O T I O N

STOR

AG

E

STO

RA

GE

GROUP 2GROUP 1

GROUP 4GROUP 3

D A T A A T R E S T

INTERNETOF

ANYTHING

SAS Models that were built on Historical Data Can be moved closer to the “Edge” of a modern data application.

ESP

ESP


Edge Analytics - On Premise and In the Cloud

STOR

AG

E

STO

RA

GE

GROUP 2GROUP 1

GROUP 4GROUP 3

D A T A A T R E S T

INTERNETOF

ANYTHING

C L O U D

O N P R E M I S E

STOR

AG

E

STO

RA

GE

GROUP 2GROUP 1

GROUP 4GROUP 3

D A T A A T R E S T

ESP

ESP

ESP

HDP

HDP

And, it should be noted that with SAS and HDP organizations are executing Machine Leaning and Deep Historical Closed Loop Analytics in the Cloud and Data Center as well.

Deep HistoricalAnalysis

MachineLearning


SAS ESP Nifi Processors – “Drag and Drop” Integration

SAS ESP Nifi Processors

enable seamless “Drag and

Drop” integration

within any HDF Workflow

SAS ESP Nifi Processors comes

within SAS ESP 4.1 which went GA

in September 2016


HDF and SAS ESP can extend outside the Data Center

Sensors & Actuators

Edge Gateways w Data Aggregation

and Filtering

Streaming Analytics and Computing

• Data Flow Management• Simple Event Processing• Complex Event Processing

Regional and Central Data Centers & the Cloud

• Event Stream Processing• Scalable Storage• Big Data Analytics

Sources or“Things”

People, Planes, Cars, Machines,

Buildings, ….

MiNiFi

Client Libraries

HDF and SAS ESP Extend Beyond Traditional Data Center Firewalls:

HDF offers Data Plan of Control – HDF offers Apache Nifi, Minifi and Client Libraries, Minifi and Nifi

SAS ESP compliments HDF by providing “Complex Event Processing” anyway along the “Data Plan of Control”

SOURCES REGIONAL AND CORE INFRASTRUCTURES

ESPESPESP

ESP


Edge Analytics Value Summary


Summary

Why Move Streaming Analytics Further out to the Edge?

Reacting immediately to an important “Event” closer to the “Edge” can yield significant positive results by:

• Increasing Customer Loyalty and Revenue

• Example: Providing a personalized, appealing offer that generates a close.

• Reducing Operational Inefficiencies and Expenses

• Examples:

• Stopping Fraud as it occurs instead

• Catching an early warning which alerts for immediate maintenance

• Only storing relevant events

• Enriching data as it is ingested

HDF and SAS ESP are integrated to allow an organization to implement specific edge streaming usage cases to improve bottom line results.


Thank You!

Mark Lochbihler

[email protected]

@MarkLochbihler

hortonworks.com/partner/sas/

sas.com/hortonworks

To learn more about our partnership, visit us at:

C o p y r ig ht © 201 6, SAS In st i tute In c. A l l r ig hts r ese rve d.

#AnalyticsX

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