big data enabled: how yarn changes the game

Grab some

coffee and

enjoy the

pre-show

banter before

the top of the

hour!

The Briefing Room

Big Data Enabled: How YARN Changes the Game

Twitter Tag: #briefr The Briefing Room

Welcome

Host: Eric Kavanagh

[email protected] @eric_kavanagh


  Reveal the essential characteristics of enterprise software, good and bad

  Provide a forum for detailed analysis of today’s innovative technologies

 Give vendors a chance to explain their product to savvy analysts

  Allow audience members to pose serious questions... and get answers!

Mission


Topics

This Month: HADOOP ECOSYSTEM

February: DATA IN MOTION

January: ANALYTICS


History is being rewritten once again…

“90% of the code that exists today should be thrown away.” Dr. Michael Stonebreaker on DM Radio, 2011


Analyst: Robin Bloor

Robin Bloor is Chief Analyst at The Bloor Group

[email protected] @robinbloor


RedPoint Global

RedPoint Global is a data management and integrated marketing technology company

RedPoint Data Management offers solutions designed for master data management (MDM), collaboration and architecture integration

RedPoint’s Hadoop-powered, YARN-compliant Marketing Application helps users monetize big data assets


Guest: George Corugedo

George Corugedo is Chief Technology Officer & Co-Founder at RedPoint Global Inc. A mathematician and seasoned technology executive, George has over 20 years of business and technical expertise. As co-founder and CTO of RedPoint Global, George is responsible for leading the development of the RedPoint Convergent Marketing Platform™. A former math professor, George left academia to co-found Accenture’s Customer Insight Practice, which specialized in strategic data utilization, analytics and customer strategy. Previous positions include director of client delivery at ClarityBlue, Inc., a provider of hosted customer intelligence solutions to enterprise commercial entities, and COO/CIO of Riscuity, a receivables management company specializing in the utilization of analytics to drive collections.

The Future is NOW with Big Data January 2015

11 © RedPoint Global Inc. 2015 Confidential

The Big Data Monetization Cycle


Gartner Emerging Technologies Hype Cycle - 2014


CEO Largest Supporter of Big Data Efforts

47%

34%

29%

27%

24%

21%

20%

19%

18%

14%

10%

4%

CEO

Line of Business (as head)

Board of Directors

Marketing

Finance/Accounting

Strategy

Engineering

Sales

Research & Development

Customer Service

None (this is an IT-only initiative)

Not sure

Q. Which of the following business groups are supporting or sponsoring your big data efforts? BASE: Plans to deploy/implement big data projects. Source: IDG Enterprise Big Data Study, 2014


“Big Data” Investments through 2017


Laying the Groundwork for Big Data Monetization

38%

37%

34%

30%

28%

27%

26%

26%

Developing or buying software applications

Investing in additional server or storage hardware/software

Hiring staff with analytics skills

Utilizing an open source software framework (e.g., Apache

Migrating to cloud-based services for storage

Increasing network bandwidth

Migrating to cloud-based services for analytics

Contracting outside big data expertise

Q. Which of the following is your organization doing to manage big data initiatives? BASE: Plans to deploy/implement big data projects.

Source: IDG Enterprise Big Data Study, 2014


Fields with Highest Interest in Big Data

Marke/ng Health Care Financial Services Pharmaceu/cals Government/Intel


Modern Marke/ng Architecture

RedPoint’s Hadoop Powered Marketing Application

RedPoint Data Management RedPoint Data Management





Consumer or En+ty Data

Opera+onal Data

Enhancement Data

Device Data

New Data



Modern Data Architecture




Opera+onal Data

Enhancement Data

Device Data

New Data





RedPoint Interac/on RedPoint Interaction







Opera+onal Data

Enhancement Data

Device Data

New Data







Opera+onal Data

Enhancement Data

Device Data

New Data

Microsites

Paper Mail

Web

Social Media

SMS or Push

Personal URL

Email

PoS

Mobile App


Orchestra/on Layer

SoMw

are De

velope

rs Kit (SDK

) Ad

apters

Conn

ectors

Plug-‐In

s Extend

ers






Opera+onal Data

Enhancement Data

Device Data

New Data

Microsites

Paper Mail

Web

Social Media

SMS or Push

Personal URL

Email

PoS

Mobile App


Glob

al Goal O

p/miza

/on

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Orchestra/on Layer




SoMw

are De

velope

rs Kit (SDK

)

RedPoint Interac/on

RedPoint Data Management

Microsites

Paper Mail

Web

Social Media

SMS or Push

Personal URL

Email

PoS

Mobile App

RedPoint Interaction



Opera+onal Data

Enhancement Data

Device Data

New Data

The RedPoint PlaVorm

Adapters

Conn

ectors

Plug-‐In

s Extend

ers


Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Goal Op/mized

Orchestra/on Layer




SoMw

are De

velope

rs Kit (SDK

)

RedPoint Interac/on


Microsites

Paper Mail

Web

Social Media

SMS or Push

Personal URL

Email

PoS

Mobile App




Opera+onal Data

Enhancement Data

Device Data

New Data


Adapters

Conn

ectors

Plug-‐In

s Extend

ers


Glob

al Goal O

p/miza

/on

Orchestra/on Layer




SoMw

are De

velope

rs Kit (SDK

)

RedPoint Interac/on


Microsites

Paper Mail

Web

Social Media

SMS or Push

Personal URL

Email

PoS

Mobile App




Opera+onal Data

Enhancement Data

Device Data

New Data


Adapters

Conn

ectors

Plug-‐In

s Extend

ers



Master Key Management

ETL & ELT Data Quality

Web Services Integra/on

Integra/on & Matching

Process Automa/on & Opera/ons

•  Profiling, reads/writes, transforma/ons

•  Single project for all jobs

•  Cleanse data •  Parsing, correc/on • Geo-‐spa/al analysis

• Grouping •  Fuzzy match

•  Create keys •  Track changes • Maintain matches over /me

•  Consume and publish • HTTP/HTTPS protocols •  XML/JSON/SOAP formats

•  Job scheduling, monitoring, no/fica/ons

•  Central point of control • Meta Data Management


Leader in both traditional and Hadoop based Data Management

First and only YARN compliant ETL/data quality toolset on the market – brings together both Big Data and tradi/onal data to create Big Informa/on!

•  Customer or Party Data

•  Processing Speed •  Match Quality

•  Ease of Use

by in: RANKED

#1

Prior to Hadoop •  100% func/onality works on both Hadoop

and tradi/onal db’s

•  Pure YARN applica/on; only one in the market for DQ/ETL/ELT

•  Single implementa/on can work across Hadoop and tradi/onal db’s.

•  Any job can be pure Client server, pure Hadoop or hybrid

With to Hadoop


One customer interaction tool: Manage end-to-end process, increase engagement

Planning & Collabora/on

Real-‐/me decisions

Targe/ng & Interac/on Design

Dashboards & Calendars

Message Design & Delivery Analy/cs & Repor/ng

• Role-‐based views • Filterable calendars

• Plans & budgets • Social workspaces • Approvals

• Personaliza/on during live interac/ons

• Factor in iden/ty & context

• Target selec/on • Offer assignment • Mul/-‐step dialogues

• Message composi/on • Landing pages • Email delivery • APIs for channel integra/on

• Visual selec/on, scoring, A/B/n tes/ng, reports

• Or use outside products

KEY FEATURES OF REDPOINT INTERACTION

Across all channels: inbound, outbound, digital,

tradi/onal


Forrester CCCM Wave Report - Leader

Debut in leader wave

#1 in Customer Sa/sfac/on

#1 in Cross Channel Integra/on

#1 in product strategy/roadmap

#1 User Interface


Debra’s Profile David’s Profile

Best Channels for Debra

Best Offers for Debra

What Local Optimization Looks Like

Op+miza+on Engine:

Marketer

Best Offers for David

How do I “locally op/mize” my ac/ons to create customer-‐obsessed campaigns?

Preferred Customer Code

Gender | Birthday | Tweets | Instagram Posts | Tumblr Likes | Purchase History | Product Viewing History | Shopping Cart Items

Customer Data

Web Mobile

Best Channels for David +

+


…and it can be easy


Data Lake Architecture for the Modern Marketing Architecture


The Big Data Monetization Cycle

Data: •  All data no matter type, format, cadence,

source, format or lack of format

•  Entities resolved and persistent keys generated

•  Complete entity profiles maintained

Analytics: •  Offline analytic parallelized for the Data Lake

•  Inline analytics for real time, unattended learning and optimization

•  Utilization of all available data at all decision points

Execution: •  Single point of operational control across all

traditional and real time channels

•  Bi-directional API’s both push to and draw results from the channels

•  Defragmentation of data, process and execution


Summary

•  Hadoop is now prac/cal and necessary in advanced marke/ng environments.

•  Use a Data Lake at the core of your marke/ng data strategy.

•  Use a tool that gives you agility and ease of use so your people are as produc/ve as quickly as possible.

•  Paralleliza/on is where Hadoop compute power comes from; use tools that leverage it properly.


Perceptions & Questions

Analyst: Robin Bloor

Robin Bloor, PhD

Hadoop is Not a Solution

However, it is a useful and increasingly versatile component for

Corporate Data Management

IT HAS BECOME “STRATEGIC”

Hadoop Evolution (The YARN Story)

FROM TO

§  Serial batch workloads

§  MapReduce §  Versatile data

storage §  Key-value access

only §  Island of processing

§  Multiple concurrent workloads

§  Multiple algorithms §  “Optimized” data

storage §  SQL, JSON & even

SPARQL access §  Integrated processing

Data & Data Life-Cycle Management

The Industrialization of Data

Hadoop(Staging

Area)

DataAssaying

Servers

The Cloud

DesktopsMobile

Devices

IoT

DataExploration

DataCapture

The Prospecting Domain

Real-TimeActioning

DataManagement

HadoopArchive

DataServing

DataLife Cycle

Mgt

SystemManagement

AppsAppsAppsDataStoreData

StoreDataStores

The New Windows

Hadoop is the new “NEW WINDOWS” The base capability is immature,

BUT: THE MARKET HAS ADOPTED IT

And vendors (like RedPoint) are filling the capability gaps

u  In the area of Hadoop enhancement, what is the most pressing need your customers come to you for?

u  What else are those customers seeking in respect of operational capabilities? In other words, what else do they complain about?

u  Do you see saving money as the primary driver for Hadoop adoption?

u  How much Hadoop use do you see which is not analytics?

u  Do you expect to have to compete with new Open Source initiatives?

u  What impact do you see the Cloud having on Big Data?

u  Who do you partner with and compete with?


Upcoming Topics

www.insideanalysis.com

This Month: HADOOP ECOSYSTEM

February: DATA IN MOTION

January: ANALYTICS


THANK YOU for your

ATTENTION!

Some images provided courtesy of Wikimedia Commons and Wikipedia

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