big data trends - worldfuture 2015 conference

BIG DATA TRENDS

July 25, 2015 David Feinleib

THE BIG DATA GROUP, LLC THEBIGDATAGROUP.COM

Copyright © 2012-2015 The Big Data Group, LLC. All Rights Reserved.

Actionable Insights From Big Data

My Background

! Managing Partner, The Big Data Group !Author of Big Data Demystified and Big Data

Bootcamp !Producer of The Big Data Landscape

! Serial entrepreneur with acquisitions by Keynote, HP and EMC !CEO & Founder, Content Analytics, a leader in

E-Commerce analytics ! General Partner, Mohr Davidow Ventures ! Group Program Manager, Microsoft

My Background

2


Agenda

• Big Data Overview

• The Big Data Landscape

• Big Data Industry Transformation

• Case Studies

• Big Data Futures

3


METADATA GROUPMETADATA GROUP

THE BIG DATA LANDSCAPE


Vertical

Ad/MediaOperational Intelligence

Business Intelligence

Analytics and Visualization

Data As A Service

[email protected] © 2012-2015 The Big Data Group, LLC bigdatalandscape.com

Analytics

Infrastructure

Operational As A Service Structured DB

Apps

Consumer

JULY 2015

mailto:[email protected]


6

64%of companies

planned to fund a Big Data Project in

2013 with more than $1M

GOOD INTENTIONS:

[Gartner 2012]

85%of the Fortune 500 still won’t be able

to use Big Data for competitive

advantage in 2015

REALITY:

[Gartner 2012]

35%Shortfall in data-savvy

workers needed to make sense out of

big data by 2018

PEOPLE:

[McKinsey 2011]

Big Data Challenges + Opportunities

6

Actionable Insights 7

Source: http://www.cnbc.com/id/101618128

http://www.cnbc.com/id/101618128


WHAT IS BIG DATA?

8

Actionable Insights From Big DataTHEBIGDATAGROUP.COM

9

Actionable Insights From Big Data 10


+

Global Positioning System (GPS) Watch

11



BIG DATA DEFINED



The Three V’s

• Volume: The amount of data

• Variety: Different types of data

• Velocity: Speed of processing the data

13


Source: datasciencecentral.com

The Three V’s

http://datasciencecentral.com


"Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the strictures of your database architectures. To gain value from this data, you must choose an alternative way to process it.”

- Ed Dumbill, O’Reilly

15


Data Is Growing at 40% Annually

16


80% of Data Is Unstructured

17

Source: www.slashroot.in

http://www.slashroot.in


18


Facebook

UsersIn Millions

0

350

700

1050

1400

Aug-04 Feb-07 Jul-09 Jan-12 Jun-14

Sources: benphoster.com, statista.com, Facebook newsroom

19

http://benphoster.com

http://statista.com


Big Data: By The Numbers

• Walmart handles 1M transactions per hour

• Google processes 24PB of data per day

• AT&T transfers 30PB of data per day

• 90 trillion emails are sent per year

• World of Warcraft uses 1.3PB of storage

20



BIG DATA INDUSTRY TRANSFORMATION



Transformation of Retail

22

SalesData driven pricing and

recommendations

THEN... NOW...

Image: webdesignerdepot.com


Transformation of Financial Services

THEN... NOW...

Manual trading

Automated, high frequency trading

23


Chart: Zendesk

Transformation of Customer Service

THEN... NOW... Unhappy

customersCustomer insight

24


Transformation of Online Marketing

Company First Last Oppty Created

Acme Fred Langan $250K 6/08/12

BigCo Tom Jones $100K 6/17/12

DealCo Jan Sedor $50K 7/01/12

Stor Works Liza Grear $750K 7/14/12

RF Group Carl Tomer $47K 7/18/12

LeadsMarketing and Sales Recommendations

THEN... NOW...

CampaignRecommendations

25


Transformation of Transportation

THEN... NOW...

You Drive You’re Driven

26


Transformation of Cities

THEN... NOW... Traditional

infrastructure

Smart meters,smart transport,

data driven city design

27


Transformation of Health + Fitness

THEN... NOW... Manual tracking

Goals + measurement

Images: Azumio, DrChrono, Fitbit, Garmin, Nike

Walk 45 minutes Smoothie Lift weights 20 minutes

28


Transformation of Education

THEN... NOW...

Linear learning Adaptive learning

Images: Khan Academy, Knewton, Michigan

29



THE BIG DATA CYCLES



The Big Data Cycle

1) Consumer scale and speed requirements have introduced new technologies that have increased the efficiency of using Big Data

2) This increased efficiency is leading to adoption of Big Data across a wide variety of industries

3) This results in the generation and consumption of more data

1

2

3

31


Big Data Technology: Hadoop + MapReduce

32

Source: Apache Software Foundation


Big Data: Shift From Technology To Information

20101990 INFORMATION

TECHNOLOGY

CommodityCompetitive Advantage

CommodityCompetitive Advantage

33



VISUALIZATION: GIVING MEANING TO DATA



Visualization Futures

• Visualization makes Big Data accessible to a much broader group of users

• Interactive visualizations will be expected

• Visualization will become the standard way to interact with data

• The sharing nature of social media is making it easier and more important than ever to present data visually

35


From Data To Insights

Hadoop + MapReduce

Visualization


Geographic Visualization: Pizza Chains in US

Source: FlowingData


Geographic Visualization: Sports Fans in US

Source: FlowingData


Visualization Humor

Source: amba12.wordpress.com

http://amba12.wordpress.com



BUSINESS EXAMPLES



Connected Car(Splunk)


• OpenXC is Ford’s open hardware, open software platform for getting real-time data from your vehicle

• You can think of OpenXC as an application programming interface (API) for your car

42

The Platform

http://openxcplatform.com/

New eCommerce Product Launch(New Relic)


Campaign / Purchase Correlation

Telecom: Reducing ChurnCase Study


46

➔ Network data➔ Service data➔ Subscriber data

BIG DATA SOURCES

400%market growth expected in the communications sector

for big data technology.*

*ARI BANERJEE, HEAVY READING, JANUARY 2014

➔ Churn management➔ Customer experience management➔ Handset analysis➔ Roaming management➔ Revenue management➔ Interconnect billing verification➔ Content settlement assurance

BIG DATA USE CASES

Big Data For Telecommunications

46


• Business Goal: Churn reduction • Predict those most likely to churn & execute proactive retention campaign

• Analytic Technique: Behavioral analysis • Identify correlations between demographics,

usage locations, call experience &consumer behavior

• Big Data Sources: OSS & BSS• Call Detail Record Data in Hadoop• Subscriber Details stored in Database

Business Opportunity: Churn Reduction

47


• Connected car: Platform approach

• Marketing analytics: Faster iterations

• Telecom: Identifying customers at risk for churn

48

Case Studies Summary



BIG DATA 2025


50

Web Browser Market Share

“Increased Accessibility has Created an Expectation that Millennials Can Have Whatever They Want Whenever They Want It”

Sources: http://thenextweb.com/entrepreneur/2014/03/29/meet-millennials-consumers-change-marketing-landscape/2/ http://www.edelman.com/news/study-finds-millennial-generations-power-to-influence-is-increasing/ forbes.com

Millennials are the first generation to grow up inherently digital

http://www.edelman.com/news/study-finds-millennial-generations-power-to-influence-is-increasing/

http://forbes.com

51

It took 19 years (1994-2013) for E-Comm Sales to Exceed $1T But Only Three Years to Nearly Double That ($2T)

52

Web Browser Market Share Next Generation of Sharing Economy

• eBay made trusting strangers possible

• Amazon, Apple and Paypal made it safe to do business online

• Apple and Google provided GPS and Internet phones to make us reachable + findable

• Facebook makes it more likely that people are who they say they are

Now the next generation of the sharing economy is being built on top of those foundations

53

Web Browser Market Share Big Data Innovation: Self-Driving Car


• Small Data the New Big Data

• Internet of Things (IoT) — Connected World

• Self-Driving Car

• E-Commerce Efficiency

• Next Generation of Sharing Economy

54

Big Data 2025 — Driven by Consumer Demand



FOR MANY COMPANIES,THE BEST OF BIG DATA IS STILL AHEAD



Contact Information

56

David Feinleib [email protected]

mailto:[email protected]