Databases Reference
In-Depth Information
• Exploratory data analysis
• Visualization (for exploratory data analysis and reporting)
• Dashboards and metrics
• Find business insights
• Data-driven decision making
• Data engineering/Big Data (Mapreduce, Hadoop, Hive, and Pig)
• Get the data themselves
• Build data pipelines (logs→mapreduce→dataset→join with other
data→mapreduce→scrape some data→join)
• Build products instead of describing existing product usage
• Hack
• Patent writing
• Detective work
• Predict future behavior or performance
• Write up findings in reports, presentations, and journals
• Programming (proficiency in R, Python, C, Java, etc.)
• Conditional probability
• Optimization
• Algorithms, statistical models, and machine learning
• Tell and interpret stories
• Ask good questions
• Investigation
• Research
• Make inferences from data
• Build data products
• Find ways to do data processing, munging, and analysis at scale
• Sanity checking
• Data intuition
• Interact with domain experts (or be a domain expert)
• Design and analyze experiments
• Find correlation in data, and try to establish causality
