ba575 week 1 business analytics and data science
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Data Exploration and VisualizationBA 575
Business Analytics and Data Science
Evan Smouse, PhD
Oregon State University
College of Business
Winter 2016
BA 575 Goals
Understand the role of data exploration and visualization in data driven decision making
Understand how data scientists think, discover ideas, answer questions and solve problems
Know how to do some of the things that data scientists do every day
Identify your own unique abilities to make sense of data
Understand how to manage data science activities to answer business analytics questions
Week 1 Topics
Course Overview
Data and Data Sources
Business Analytics From a Data Scientist’s Point of View
A Story and a Look at Some Data
Tools Lab
The Economist
The Economist
Where Are the Data Scientists?
McKinsey
Statisticians Have Sexy Jobs
“I keep saying the sexy job in the next ten years will be statisticians. People think I'm
joking, but who would've guessed that computer engineers would've been the
sexy job of the 1990s?”Hal Varian, Google’s Chief Economist
Hal Varian Explains
“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's going to be a hugely important skill in the next decades, not only at the professional level but even at the educational level for elementary school kids, for high school kids, for college kids. Because now we really do have essentially free and ubiquitous data. ”
Sexy Skills of Data Geeks
1. Statistics (studying)– traditional analysis you're used to thinking about
2. Data Munging (suffering)– parsing, scraping, and formatting data
3. Visualization (story telling)– graphs, pictures, interactivity, …
Michael Driscol
Computational Information Design Model
Ben Fry
Rise of the Data Scientist
“This need for data scientists is quite evident in business applications where educated decisions need to be made swiftly. A delayed decision could mean lost opportunity and profit. Terabytes of data are coming in whether it be from websites or from sales across the country. But in an area where Excel is the tool of choice (or force), there are limitations, hence all the tools, applications, and consultancies to help out. This of course applies to areas outside of business as well.”
Nathan Yau: Flowing Data
Rise of the Data Scientist
“Basically, the more you learn, the more you can do, and the higher in demand you will be as the amount of data grows and the more people want to make use of it.”
Nathan Yau: Flowing Data
What is Data Science?
Drew Conway Venn diagram
Is Data Science Real?
“I took the initiative in creating the Internet”
- former US Vice President Al Gore
Is Data Scientist a Real Job?
“When Jeff Hammerbacher and I talked about our data science teams, we realized that as our organizations grew, we both had to figure out what to call the people on our teams. Business Analyst seemed too limiting. Data Analyst was a contender … The term that seemed to fit best was Data Scientist: those who use both data and science to create something new.”
DJ Patil – formerly at LinkedIn; Jeff Hammerbacher was at Facebook
What Makes a Good Data Scientist?
Technical expertise: the best data scientists typically have deep expertise in some discipline
Curiosity: a desire to go beneath the surface and discover and distill a problem down into a very clear set of hypotheses that can be tested
Storytelling: the ability to use data to tell a story and to be able to communicate it effectively
Cleverness: the ability to look at a problem in different, creative ways
DJ Patil
Skills That Good Data Scientists Have
Finding rich data sources
Working with large volumes of data despite hardware, software, and bandwidth constraints
Cleaning the data and making sure that data is consistent
Melding multiple datasets together
Visualizing that data
Building rich tooling that enables others to work with data effectively
Skills That Good Business Analysts Have
Finding rich data sources
Working with large volumes of data despite hardware, software, and bandwidth constraints
Cleaning the data and making sure that data is consistent
Melding multiple datasets together
Visualizing that data
Building rich tooling that enables others to work with data effectively
The Same Skills
Applied to
Business Problems!
Profile Yourself
Assign a total of 100 points to your own skill levels in these domains:
Business
Machine Learning & Big Data
Mathematics
Programming
Statistics
Data Science Profile
Business: Business, Product Development
Machine Learning/Big Data: Big and Distributed Data, Machine Learning, Structured Data, Unstructured Data
Math: Algorithms, Bayesian/Monte Carlo Statistics, Graphical Models, Math, Optimization, Simulation
Programming: Back-end Programming, Front-end Programming, Systems Administration
Statistics: Classical Statistics, Data Manipulation, Science, Spatial Statistics, Surveys and Marketing, Temporal Statistics, Visualization
Web-Based Survey of Data Scientists
Harlan Harris
The Clusters
Data Businessperson: Business person, Leader, Entrepreneur
Data Creative: Artist, Jack-of-All-Trades, Hacker
Data Researcher: Scientist, Researcher, Statistician
Data Engineer: Engineer, Developer
Profile Yourself
Assign a total of 100 points to your own skill levels in these domains:
Business
Machine Learning & Big Data
Mathematics
Programming
Statistics
Next: A Story and a Look at Some Data