Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17...

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Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae

Transcript of Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17...

Page 1: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

Ch 3. A Cross-Section of Big Data Sources and the Value They Hold

Taming The Big Data Tidal Wave

17 May 2012SNU IDB Lab.

Hye Chan, Bae

Page 2: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 3: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Telematics (1/2)

Telematics Data Receives serious attention in the auto insurance industry

– Putting a sensor, or black box to capture the current car information Helps insurance companies better understand customer risk levels Has the potential to both

– Lower insurance rates (for most drivers)– Increase profits (for insurers)

Page 4: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Telematics (2/2)

The Value of Telematics Data It's possible to answer the question like causes of traffic jams

without very focused and expensive testing It may improve our lives by reducing the stress and frustration

Page 5: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 6: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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It is one of the biggest and most common sources of big data– E-mails– Text messages– Social media postings– Instant messages– Real-time chats– Etc.

Natural language processing– Parsing text and assigning meaning to the words,

phrases and components

Text (1/4)

Text Data

Page 7: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Text (2/4)

Text Data (cont.) The results of those processes can be analyzed

– Sentiment mining– The comments about specific products from customers

Interpreting text data is quite difficult– The words change meaning based on

Emphasis (but there is no emphasis in text) Full context

Page 8: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Text (3/4)

Using Text Data Sentiment analysis

– Looks at the general direction of opinion– Understanding the trends can be immensely

valuable in planning what to do next

– For a product, positive or negative is valuable information If the customer hasn't yet purchased that product

Page 9: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Text (4/4)

Using Text Data (cont.) Pattern recognition

– Complains, repair notes, other comments– An organization will be more quickly able to identify and fix problems

Before they become bigger issues

Fraud detection– A major application for text data– Within health insurance

It's possible to use text analysis to parse out the comments and justifications

Page 10: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 11: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Time and Location (1/3)

Time and Location Data Time and location information is a growing source of data

– GPS (Global Positioning Systems)– Cellular phones

Tracking the routes– You can track the exact routes you travel

When you exercise How long the routes are How long it takes you to complete the routes

Page 12: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Time and Location (2/3)

The Value of Time and Location Data Local police and fire agencies

– Provide information on where they typically travel with Real time information Accurate location

Time- and location-sensitive offers– This is going to be huge in the future of marketing

Page 13: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Time and Location (3/3)

The Value of Time and Location Data (cont.) Enhancing social network analysis

– Time and location data allows identification of what people were at the same place at the same time

Who attended a given concert or movie? Who was dining at a specific restaurant at the same time?

– It is possible to identify people who may not know each other But who have a lot of common interests Imagine a dating service with this information!

Page 14: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 15: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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RFID (1/4)

RFID Data Radio Frequency Identification(RFID) tag

– A small tag placed on objects– It contains a unique serial number (different from UPC code)

RFID reader can read the tag– by sending out and receiving back a signal

Page 16: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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RFID (2/4)

Using RFID Data Identifying "restocking" situation on the shelf

Storage room

Page 17: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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RFID (3/4)

Using RFID Data Identifying "restocking" situation on the shelf

Storage room

Page 18: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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RFID (4/4)

Using RFID Data (cont.) Product tracking system

Page 19: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 20: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Smart-Grid (1/2)

Smart-Grid Data The next generation of electrical power infrastructure

– much more advanced and robust Has highly sophisticated

– Monitoring– Communications– Generation systems

Enable more consistent service and better recovery from outages

Page 21: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Smart-Grid (2/2)

The Value of Smart-Grid Data The smart-grid data will benefit all

– Consumers will have customized rate plans– Utilities will have much better forecasts of demand– Household or business will gain the power

Page 22: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 23: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Sensor (1/2)

Sensor Data There are a lot of complex machines and engines

– Aircraft, trains, military vehicles, etc.– Keeping running smoothly is critical given how much it costs– Embedded sensors have begun to be utilized in everything

Monitoring– It's worth capturing as much detailed

data as possible– It's quite expensive to replace a

flawed component once an engineis released

Page 24: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Sensor (2/2)

The Values of Sensor Data It's possible to pinpoint specific patterns

– Patterns that lead to imminent failures Strategies for minimizing down time

– Holding spare parts or engines– Creating diagnostics to quickly identify the parts that must be replaced– Investing in more reliable versions

Page 25: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 26: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Telemetry (1/2)

Telemetry Data Telemetry is the term used in the video game industry

– To describe the capture of in-game activities In a hockey game

– Where a player was when a shot on goal was taken– What type of shot is was– What speed the shot had

Telemetry data makes it possible for game producers to know in-timate details about– How customers actually play and interact with the games

Page 27: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Telemetry (2/2)

Using Telemetry Data In video games

– Maintaining renewal rates is absolutely critical Many games make money through subscriptions

– Customer satisfaction is a big issue For casual gamer: a game is easy For hardcore gamer: a game is too hard

Page 28: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Outline Telematics Text Time and Location RFID(Radio Frequency IDentification) Smart-Grid Sensor Telemetry Social Network

Page 29: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Social Network (1/3)

Social Network Data Social network data qualifies as a big data source

– Social network analysis looks into several degrees of association A phone company

Company

Traditional data

Company

Social network dataSocial network analysis

Per-son

Per-son

Per-son

Per-son

Per-son

Per-son

Per-son

Per-son

Page 30: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Social Network (2/3)

The Value of Social Network Data A traditional wireless carrier

A modern wireless carrier

Low-value customer

Let him go

The customer isn't worththe cost of saving

Heavy user who have wide networks of friends

Do not let him go

Page 31: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

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Social Network (3/3)

Using Social Network Data Identification of highly connected customers can pinpoint

– He can influence brand image– Highly connected customers can be provided perks, advance trials, and

other goodies Advertisement in social networking sites

– social network analysis can yield insights into what advertisements might appeal to given users

Based on knowing what their circle of friends has an interest in

Advertisement?

Friend

I like to ride a bike!

Page 32: Ch 3. A Cross-Section of Big Data Sources and the Value They Hold Taming The Big Data Tidal Wave 17 May 2012 SNU IDB Lab. Hye Chan, Bae.

Thank you