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From Big Data Management
to Big Data Science
1
What is next?
Real big data is widely available
Only a few people know how to deal with it
You’re now one of them
Applications
The project is a start
Keep your hands dirty
Consider using the public cloud (e.g., AWS,
Google Cloud, or Microsoft Azure)
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Job Market
https://www.techicy.com/5-best-programming-languages-to-watch-out-in-2019-for-data-science.html
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Data Science
Credits: Drew Conway 4
Data Science
https://mashimo.wordpress.com/2016/05/28/big-data-data-science-and-machine-learning-explained/
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Data Scientist
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Next Steps
CS
Big data tools
Python/R/Scala
Math/Stats
Linear algebra
Correlation analysis
Hypothesis tests
Collaboration with domain experts
Visualization
Prototyping
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CS
https://www.slideshare.net/galvanizeHQ/how-to-become-a-data-scientist-by-ryan-orban-vp-of-operations-and-expansion-galvanize
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CS/Big Data
https://www.slideshare.net/galvanizeHQ/how-to-become-a-data-scientist-by-ryan-orban-vp-of-operations-and-expansion-galvanize
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Math/Stats
https://www.slideshare.net/galvanizeHQ/how-to-become-a-data-scientist-by-ryan-orban-vp-of-operations-and-expansion-galvanize
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Online Courses
https://www.slideshare.net/galvanizeHQ/how-to-become-a-data-scientist-by-ryan-orban-vp-of-operations-and-expansion-galvanize
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Data Analytics
https://www.slideshare.net/galvanizeHQ/how-to-become-a-data-scientist-by-ryan-orban-vp-of-operations-and-expansion-galvanize
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Big Data Landscape
Distributed
StorageHDFS
KV
stores
LSM
trees
Column
stores
Query
Processing
Map
ReduceRDD Hyracks
High level
APIsPig
Latin
Spark
SQLHBase
Big data
packages
Algebricks
MLlib GraphX SparkR
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