cap4773/cis6930 projects in data science, fall 2014 .... data science... · cap4773/cis6930...
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CAP4773/CIS6930 Projects in Data Science, Fall 2014 [Review] Overview of Data Science
Dr. Daisy Zhe Wang CISE Department
University of Florida August 25th 2014
Review Overview of Data Science
• Why Data Science?
• What is Data Science?
• What are some prominent examples of Data Science?
• How to become a Data Scientist?
• Who are hiring Data Scientists Now?
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The Dawn of Big Data
• Google, Yahoo today – Core Business: Web Search and Computational advertising – Google: 35,000 searches/sec – Yahoo! scale: 600 million users per month, 4 billion clicks per day, 25
terabytes of data collected every day
• Netflix 2007 – Movie recommendations – 100 million ratings, 500,000 users, 18,000 movies – netflix prize
• Amazon 2003 – Product recommendations, reviews – 29 million customers, millions of products
• Word Economic Forum 2011 at Davos – Personal data – digital data created by and about people – represents a
new economic “asset class”, touching all aspects of society.
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How Big is Your Data?
• Kilobyte (1000 bytes)
• Megabyte (1 000 000 bytes)
• Gigabyte (1 000 000 000 bytes)
• Terabyte (1 000 000 000 000 bytes)
• Petabyte (1 000 000 000 000 000 bytes)
• Exabyte (1 000 000 000 000 000 000 bytes)
• Zettabyte (1 000 000 000 000 000 000 000 bytes)
• Yottabyte (1 000 000 000 000 000 000 000 000 bytes)
It is not only about volumes!
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5 Vs of Big Data
• Raw Data: Volume
• Change over time: Velocity
• Data types: Variety
• Data Quality: Veracity
• Information for Decision Making: Value
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Multimodal Data Sources on World Cup Common
Twitter ~5M tweets with
244,000 associating images
News & Blogs 776 blog posts and associated
pictures
Youtube 460 minutes of
Videos and Audio
Flickr 913 images and
associated captions Facebook
250 posts and associated images
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Google Images 1,920 images
and associated captions
Current Trends
• Applications has bigger data and need more advanced analysis – Example: Web, Corporate documents and Emails
• Natural Language Processing
– Example: Social Media • Network/Graph Analysis
• IT Infrastructure moving to Cloud Computing (2006) – Parallel Computing, SaaS – Elastic Computing – pay-as-you-go, scale up/down
• Data Science arise given this application pull and
technology push (2011) 26
Data Science – A Definition
Data Science is the science which uses computer science, statistics and machine learning, visualization and human-computer interactions to collect, clean, integrate, analyze, visualize, interact with data to create data products.
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Data to Data Products
• Web Text Data Knowledge Bases with Facts & Relationships
• Twitter Text/Images Real-time Events and News
• Knowledge bases first-order inference rules and constraints
• Text Data, Social Media Data Product Review and Consumer Satisfaction
• Software Log Data Automatic Trouble Shooting
• Genotype and Phenotype Data common patterns New treatment for Cancer
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Other Data Products
• Financial products for investment or retirement funds
• Legal profession uses e-discovery tool for retrieval and review of legal documents
• Political campaign management
• Sports (e.g., Oakland baseball team)
• Remote Sensing for Environment Monitoring
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Data Products – Google
• Web Search
• Google Ads
• News Recommendation Engine
• Google Maps
Currently one of the best if not the best IT company to work for. (Google event on Jan 21/22)
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Data Products – Netflix
• Personalized Movie Ratings
• Movie Recommendations
• Similar Movies
• Movie Categories (e.g., 80’s movie with a strong female lead, Kung Fu movies)
BlockBuster is out of the business …
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Data Products – LinkedIn/Facebook
• People you may know
• Applications you may like
• Jobs/Events you might be interested
• Classifier for bad users and bad content
• With high accuracy, Facebook can guess whether you are single or married
Who does not have LinkedIn/Facebook Account?
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Data Products – Twitter
• Text Analysis – Spam Filter/Similarity Search
• User Sentiment/Satisfaction/Feedback
• News Breakout
• Trend and Topics
200 million users as of 2011, generating over 200 million tweets and handling over 1.6 billion search queries per day
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Data Products – Splunk
• Degradation, Failure Detection
• Identify Security Breach
• Event Monitoring
• Troubleshoot Tools
• Cross-platform Event Correlation
Founded 2004, IPO in 2012
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The Life of Data (state-of-the-art)
Collect Clean Integrate Visualization
Interface
Users
Data Sources
Analysis
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Challenges in Data Science
• Find Data (Data Collection, Quality)
• Prepare Data (Noisy, Incomplete, Diverse, Streaming …)
• Analyze Data (Scalable, Accurate, Real-time, Advanced Methods, Probabilities and Uncertainties ...)
• Represent Analysis Results (i.e. data product) (Story-telling, Interactive, explainable…)
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Skill Set of a Data Scientist
• Data Management – Data collection, storage, cleaning, filtering, integration
…
• Large-scale Parallel Data Processing – Parallel computing
• Statistics and Machine Learning – Data modeling, inference, prediction, pattern
recognition …
• Interface and Data Visualization – HCI design, visualization, story-telling …
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“Sexy Job” in the next 10 years
“The sexy job in the next ten years will be … The ability to take data—to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it—that’s going to be a hugely important skill.”
-- Hal Varian, Google Chief Economist, 2009
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Who’s hiring Data Scientist?
• IT companies: Google, Twitter, Lexis/Nexis, Facebook, Pivotal/EMC…
• Media and Financial sectors Fox, CNN, NYT, Bloomburg,…
• Research: Biology, Medicine, Physics, Psychology,…
• Information office in government and corporations…
• Law firms: e-discovery tools…
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Additional Reading Pointers
• Data Science Summit (Strata) (http://www.datascientistsummit.com/ )
• Kaggle Competitions (http://www.kaggle.com/)
• Data Science course at Berkeley (http://datascienc.es/ ) & on Coursera (https://www.coursera.org/course/datasci/ )
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Summary
• Why now: Dawn of Big Data <<- Need for Advanced Analytics and Cloud Computing
• What is it: Data ->> Data Product, many examples incl. Google, Netflix, Splunk, LinkedIn
• How to become: Data management, parallel computing and data processing, statistical machine learning, and visualization skills
– Life of Data
• Who are hiring: Data Scientists are in great demands, from industry to government to science.
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Announcements
• Course Website: http://www.cise.ufl.edu/class/cis6930fa14pro
• New registration slots will be available @ 4pm TODAY
– For first year MS students with no data mining background: please first take Introduction to Data Science
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Next Few Lectures • Graph Algorithms and Graph Databases
– Offline queries: page-rank over Web link structure – Online queries: SPARQL (sub-graph matching) over RDF stores
• Shortest paths (social network transactions)
• Text and Image Extraction and Retrieval – Features Extraction – Bag of Words model + Solr indexing – More advanced: Entity and event extractions/classifications
• Knowledge Base Construction, Querying, Integration and Mining – General, Health, Ecology, Medical, … – Rule/Constraint Learning – More advanced: Uncertainty Management and reasoning
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