how big companies plan to use our big data 201610

Mark Tabladillo Ph.D.

Orlando, FL 2016

Nova (PBS)

15 Years of Terror (September 7, 2016)

Cyberwar Threat (October 14, 2015)

Intro to Big Data (2016)

What is Big Data (2016)

Salaries (2015)

Retrieved October 2016 http://www.forbes.com/sites/louiscolumbus/2015/11/16/where-big-data-jobs-will-be-in-2016/#111ddf2cf7f1

Top Ten Industries (2015)

Retrieved October 2016 http://www.forbes.com/sites/louiscolumbus/2015/11/16/where-big-data-jobs-will-be-in-2016/#111ddf2cf7f1

Top Employment Markets

Alexa’s Largest Websites

Google Monitoring (2016)

Big Data Predictions (2016)

Google Revenue (2011)

YouTube (2014)

Social Media Users (2016)

Why Success Depends on Data

FOOD : DATA :: RECIPE : MODEL

Google Flu Trends (GFT): RIP

2008

• Published in Nature, searches could beat the Centers

for Disease Control by two weeks

2013

• GFT missed the flu season peak by 140 percent

• “Quietly Euthanized”

2014

• In Science, paper showed good performance for 2-3

years

• Overfitted to terms like “high school basketball”

Retrieved October 2016 https://www.wired.com/2015/10/can-learn-epic-failure-google-flu-trends/

Spurious Correlations

Spurious Correlations

We now face the next disruption –the fourth industrial revolution

IntelligenceCloudBig Data

Data is a key strategic asset

$1.6TAdditional business value captured

by companies that are leaders in

using data assets to their advantage

Source: IDC, 2014

10%Percent of organizations expected

to have a highly profitable business

unit specifically for productizing and

commercializing their data by 2020

Source: Gartner, 2016

The cloud offers limitless computing power

Speed EconomicsScale

67Years

25Years

15Years

The time to adapt to disruptions is shrinking

Source: BBC

A hundred years ago, the average lifespan of a

company listed on the S&P 500 index was 67 years

75% of the S&P 500 will be new

(not on the index today)

25% of the S&P 500 will

be ones on the index today

In the 2020s…

And incorporating industry-leadingMicrosoft solutions

Action

People

Automated Systems

Apps

Web

Mobile

Bots

Intelligence

Dashboards &

Visualizations

Cortana

Bot Framework

Cognitive Services

Power BI

Information

Management

Event Hubs

Data Catalog

Data Factory

Machine Learning

and Analytics

HDInsight (Hadoop and

Spark)

Stream Analytics

Intelligence

Data Lake Analytics

Machine Learning

Big Data Stores

SQL Data Warehouse

Data Lake Store

Data Sources

Apps

Sensors and devices

Data

Here are some examples of how our customers are staying ahead

Exploring new business

opportunities with

data-driven services

Improving visibility

and making accurate

predictions with

remote monitoring

Getting the right

products to the right

places with inventory

management

Offering customers

exactly what they want,

when they want it, with

personalization

Fixing problems

proactively before they

start with predictive

maintenance

Bing Predicts