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1© 2016 The MathWorks, Inc.
Introduction to Data
Analytics with MATLAB
David Willingham
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WITH SOFTWARE
(and smart people)
ANYTHING IS POSSIBLE
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File I/O
• Text
• Spreadsheet
• XML
• CDF/HDF
• Image
• Audio
• Video
• Geospatial
Communication Protocols
• CAN (Controller Area Network)
• DDS (Data Distribution Service)
• OPC (OLE for Process Control)
• XCP (eXplicit Control Protocol)
Real-Time Sources
• Sensors
• GPS
• Instrumentation
• Cameras
• Communication systems
• Machines (embedded systems)
Repositories
• Databases (SQL)
• NoSQL
• Hadoop
File I/O
• Text
• Spreadsheet
• XML
Web Sources
• RESTful
• JSON
• HTML
• Mapping
• Financial datafeeds
Analytics that increasingly
require both business
and engineering data
Business and
Transactional Data
Engineering, Scientific,
and Field Data
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“Data is the sword of the 21st century, those who
wield it the samurai.”
Big data — how to create
it, manipulate it, and put it
to good use.
“If you want to work at
Google, make sure you
can use MATLAB.”
Google’s Former SVP - Jonathan Rosenberg
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2017 Gartner Magic Quadrant – Data Science
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Why MATLAB?
Data
Analytics
DATA
• Engineering, Scientific, and Field
• Business and Transactional
MATLAB Analytics work
with business and
engineering data
MATLAB lets engineers do
Data Science
themselves
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Embedded Systems
Developed with Model-Based Design
Enterprise
IT Systems
MATLAB Analytics run anywhere
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MATLAB for Data AnalyticsCustomer Examples
Online optimization of building energy use
Real-time, cloud-based system
Combines analytics with optimization for
predictive control of single-building HVAC
Energy consumption reduced 15-25%
Online engine health monitoring
Real-time analytics integrated with
enterprise service systems
Predict sub-system performance (oil, fuel,
liftoff, mechanical health, controls)
Improve aircraft availability and reduce
maintenance costs
Cloud-based wheeze analysis
Medical device to monitor and
manage asthma and COPD
Leverages analytics in cloud and
embedded system
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http://www.mathworks.com/company/events/conferences/matlab-
conference-australia/2015/abstracts.html?expand=cp&#cp_session1
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Medical Devices
Aeronautics
Off-highway
vehicles
Automotive
Oil & Gas
Industrial Automation
Fleet Analytics
Health Monitoring
Asset Analytics
Process Analytics
Prognostics
Condition
Monitoring
Clean Energy
Retail Analytics
Mfg Process
Analytics
Supply Chain
Operational
Analytics
Healthcare Analytics
Risk Analysis
Logistics
Retail
Finance
Healthcare
Management
Internet
Railway Systems
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Data Analytics Workflow
Reporting and
Documentation
Outputs for Design
Deployment
ShareExplore & Discover
Data Analysis
& Modeling
Algorithm
Development
Application
Development
Files
Software
Hardware
Access
Code & Applications
Automate
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ChallengeProvide clients with an industry-first web platform for
portfolio modeling and analytics
SolutionUse MATLAB to develop and test analytics modules,
and use MATLAB Compiler SDK to deploy them into a
production .NET environment
Results Quantitative development decoupled from
interface development
Stable, responsive system deployed
Rapid delivery of new features enabled
Frontier Advisors Develops Web-Based
Platform for Portfolio Analytics
Link to user story
“MATLAB and MATLAB Compiler
SDK enabled us to rapidly deliver
a sophisticated portfolio analytics
web application with confidence
that it will return accurate results
extremely quickly, ensuring a
highly usable and stable platform
for our clients.”
Lee Eriera
Frontier Advisors
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Today’s Objectives
Introduce you to data analysis with MATLAB
Show how you can overcome common
data analysis challenges with MATLAB
Demonstrate multiple ways of sharing your
analysis and results with others
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Common Data Analysis Challenges
using Excel
Complex calculations
Messy Data
Speed of Execution
Automation
Batch Processing
Report Generation
Deployment
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Demo: Solar Radiation EstimationIntroduction to Data Analysis with MATLAB
Goal:
– Estimate daily mean global solar radiation given
low cost and easily obtained measurements
Approach:
– Process historical measurements
– Develop predictive model
– Document analysis in a report
– Apply analysis on multiple files
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Modeling Global Solar Radiation
𝑅𝑠 = 𝑎 (1 + 𝑏𝐻)(1 − 𝑒−𝑐 ∆𝑇𝑛)
extraterrestrial
radiation
total global
radiation
Solar Ratio (Rs) =Global solar radiation
Extraterrestrial solar radiation
Daily Temperature Difference (∆𝐓) = TDailyMax – TDailyMin
H is Relative Humidity
a,b,c,n are the model coefficients
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Explore & Discover
Demo SummarySolar Radiation Estimation
Reporting and
Documentation
Outputs for Design
Deployment
Share
Data Analysis
& Modeling
Files
Software
Hardware
Access
Code & Applications
Automate
Algorithm
Development
Application
Development
Products Used MATLAB
Curve Fitting Toolbox
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Machine Learning
Machine learning uses data and produces a program to
perform a task
Standard Approach Machine Learning Approach
𝑚𝑜𝑑𝑒𝑙 = <𝑴𝒂𝒄𝒉𝒊𝒏𝒆𝑳𝒆𝒂𝒓𝒏𝒊𝒏𝒈𝑨𝒍𝒈𝒐𝒓𝒊𝒕𝒉𝒎
>(𝑠𝑒𝑛𝑠𝑜𝑟_𝑑𝑎𝑡𝑎, 𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦)
Computer
Program
Machine
Learning
𝑚𝑜𝑑𝑒𝑙: Inputs → OutputsHand Written Program Formula or Equation
If X_acc > 0.5
then “SITTING”
If Y_acc < 4 and Z_acc > 5
then “STANDING”
…
𝑌𝑎𝑐𝑡𝑖𝑣𝑖𝑡𝑦= 𝛽1𝑋𝑎𝑐𝑐 + 𝛽2𝑌𝑎𝑐𝑐+ 𝛽3𝑍𝑎𝑐𝑐 +
…
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Demo: Machine Learning Using Mobile Phone Data
Machine
Learning
Data:
3-axial Accelerometer data
3-axial Gyroscope data
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Sharing Results from MATLAB
Automatically generate reports
Create and package applications
Deploy to other environments
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MATLAB Programs Can be Shared With Anyone
Share With Other MATLAB Users Share With People Who do Not Have MATLAB
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Write Your Programs Once
Then Share To Different Targets
MATLAB
C/C++ExcelAdd-in JavaHadoop .NET
MATLAB
Compiler
MATLABProduction
Server
StandaloneApplication
MATLAB
Compiler SDK
Apps Files
Custom Toolbox
Python
With MATLAB
Users
With People Who Do
Not Have MATLAB
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3rd Party Excel Add Ins for Forecasting
Challenges:
– Manual
– Automation
– Batch Processing
– Tuning (Optimizing)
– Speed of Execution
– Report Generation
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23© 2016 The MathWorks, Inc.