how big companies plan to use our big data 201610
TRANSCRIPT
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
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/
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
