UX Nights Vol XXVI Big Data y Experiencia de Usuario Transformando la vida cotidiana a través de Big Data Omar Aviles Technical Evangelist Manager - Microsoft México 6 de octubre de 2016 Ciudad de México

2. Big data is high-volume,
high-velocity and/or high-
variety information assets
that demand cost-effective,
innovative forms of
information processing that
enable enhanced insight,
decision making, and
process automation.
– Gartner, Big Data Definition*
Three plays to land big data
Advanced Analytics or Internet of Things (IoT)
“We are trying to predict when our customers churn. We are trying to get insights from our
devices in real-time, etc.”
Modernizing a data warehouse with big data
“We and want to incorporate all of our data including ‘big data” with our data warehouse”
Looking for a big data solution
“Big Data solutions + better UI/UX Experiences”

3. Big Data is driving transformative changes
Traditional
Big Data
Relational data
with highly modeled schema
All data
with schema agility
Specialized HW
Commodity HW
Data
characteristics
Costs
Culture
Operational reporting
Focus on rear-view analysis
Experimentation leading
to intelligent action
With machine learning, graph, a/b testing

4. The Big Data opportunity for

5. Roles
Data Scientist
UX Professionals
Big Data Specialist
Data Analyst

6. Why Big Data is important for us as UX professionals?
Data
Solutions
Metrics
Context
Data Collection
Analytics
Big Data
UX

7. Positioning the different
big data solutions

8. Business
apps
Custom
apps
Sensors
and
devices
People
Automated
systems
Data
Intelligence Action
Apps

9. Machine Learning
and Analytics
Big Data Stores
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
HDInsight
(Hadoop and Spark)
Stream Analytics
Intelligence
Data Lake
Analytics
Machine Learning
SQL Data
Warehouse
Data Lake Store
Data
Sources
Apps
Sensors
and
devices
Data
Big Data as part of Intelligence way to take a decision
MICROSOFTBIGDATASOLUTIONS

10. Transform Big Data Experience

11. Interactive Data Visualization

12. Holographic visualization

13. Cognitive Services
+
Big Data
Give your apps
a human side

14. Cognitive
Services
and Big
Data

15. Learn more
• Big Data and analytics
• http://bit.ly/2dGz5Ey
• Cognitive Services
• http://bit.ly/2dqOyuI
• Tech Summit Mexico City
• http://bit.ly/2cQGjKe

16. Customer Cases

17. Retail
• Real-time offers
and personalized
services
• Demand forecasting
• Sentiment analysis
Manufacturing
• Manufacturing ops
• Connected cars
Government
• Smart buildings
• Transit and traffic
optimization
Health
• Remote health
monitoring
• Population health
management
Financial Services
• Customer experience
• Risk assessment
• Clickstream and behavior
• Point of sales
• Server logs
• Sentiment and web
• Machine and sensor
• Structured and unstructured
• Sentiment and web
• Server logs
• Structured and unstructured
• Patient vitals
• Genomic data
• Server logs
• Sentiment and web
• Server logs
• Structured and unstructur
SALES PLAY #1
Advanced Analytics or Internet of Things (IoT)
Data type usage by vertical
Solutions
New types
of data

18. Customer example: Chili’s Restaurants
using Ziosk Tablets for IoT scenario
Scenario
Ziosk Tablets on every restaurant | Wanted to improve guest
satisfaction, customer insights, and restaurant efficiency
Solution
Azure HDInsight (Hadoop-as-a-service), Azure Machine
Learning, Power BI to aggregate data in real-time and identify
relationships between customer behavior and purchases
Result
• Optimize guest experience on tablets by delivering
customized offers in real-time
• Understand restaurant metrics such as customer wait times,
wait staff efficiencies, restaurant sales, etc.
SALES PLAY #1
Advanced Analytics or
Internet of Things (IoT)
“Until now, we haven’t had the ability to optimize the guest
experience based on their specific interactions with the
devices. With Azure, we can close the loop.”
Kevin Mowry, Chief Software Architect

19. Customer example: Virginia Tech crunch
endless amounts of Genomic data
Scenario
DNA sequencers are generating 15PB of genomic data each
year. Virginia Tech needed to process it to foster medical
breakthroughs including new cancer treatments. They were
evaluating creating a multimillion dollar supercomputer
center, but wanted to find a different way to process the data.
Solution
Azure HDInsight (Hadoop-as-a-service) was chosen to
process genome data resulting in significant cost savings as
they only pay for what they need.
Result
• Significant cost savings with the cloud
• Elastic scale that keeps up with huge data volumes
• Powering the search for cancer treatments
SALES PLAY #3
Looking for a big data
solution
“What excites me about what I’m doing with the cloud
(HDInsight) is the ability to accelerate discovery to the point
that we may be able to find treatments for cancer.”
Wu Feng, Professor of Computer Science

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