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Mark Tabladillo Ph.D.
Orlando, FL 2016
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610
Nova (PBS)
15 Years of Terror (September 7, 2016)
Cyberwar Threat (October 14, 2015)
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610
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)
How Big Companies plan to use Our Big Data 201610
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
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610
Spurious Correlations
How Big Companies plan to use Our Big Data 201610
We now face the next disruption –
the fourth industrial revolution
IntelligenceCloudBig Data
How Big Companies plan to use Our Big Data 201610
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
67
Years
25
Years
15
Years
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…
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610
And incorporating industry-leading
Microsoft 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
How Big Companies plan to use Our Big Data 201610
How Big Companies plan to use Our Big Data 201610

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How Big Companies plan to use Our Big Data 201610

  • 4. Nova (PBS) 15 Years of Terror (September 7, 2016) Cyberwar Threat (October 14, 2015)
  • 7. Intro to Big Data (2016)
  • 8. What is Big Data (2016)
  • 9. Salaries (2015) Retrieved October 2016 http://www.forbes.com/sites/louiscolumbus/2015/11/16/where-big-data-jobs-will-be-in-2016/#111ddf2cf7f1
  • 10. 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
  • 19. Why Success Depends on Data FOOD : DATA :: RECIPE : MODEL
  • 20. 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/
  • 29. We now face the next disruption – the fourth industrial revolution IntelligenceCloudBig Data
  • 31. 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
  • 32. The cloud offers limitless computing power Speed EconomicsScale
  • 33. 67 Years 25 Years 15 Years 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…
  • 36. And incorporating industry-leading Microsoft 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
  • 37. 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