Google Data Analytics #7_Data and Decision

Data vs. Metrics

• Data
  • collection of raw facts
• Metric
  • single, quantifiable type of data that can be used for measurement

Data-Driven vs. Data-Inspired

• Data-Driven Decision Making
• Data-Inspired Decision Making
  • explores different data sources to find out what they have in common
• Algorithm
  • a process or set of rules to be followed for a specific task

Qualitative vs. Quantative

• Quantitative Data

  • specific and objective measures of numerical facts
  • ex. structured interviews, surveys, polls

• Qualitative Data

  • subjective or explanaoory measures of qualities and characteristics
  • ex. focus group, social media text analysis, in-person interviews

Small Data vs. Big Data

• Small Data

  • specific
  • short well-defined-time-period
  • day-to-day decisions

• Big Data

  • large and less-specific
  • long time-period
  • useful for looking at large-scale questions and problems

  PROs

  • help spot the trends of patterns
  • help understand the current market conditions
  • help apply the feedbacks

  CONs

  • may overload with unimportant and irrelevant information
  • important data can be hidden
  • not always accessible
  • current tools still struggles to provide measurable data leading to unfair algorithmic bias

  The Three (or Four) V's For Big Data

  • Volume : the amount of data
  • Variety : the different kinds of data
  • Velocity : how fast the data can be processed
  • the quality and reliability of the data

  

Report vs. Dashboard

• Report

  • static collection of data given to stakeholders periodically

  PROs

  • great at giving snapshots of high level historical data for an organization
  • can be designed and sent out periodically
  • quick to design and easy to use
  • uses static data that reflects data that has already been cleaned and sorted

  CONs

  • requires continual maintenance
  • less visually pleasing
  • static; ergo, does not reflect real-time

  Pivot Table_spreadsheet

  • a data summarization tool that is used in data processing to sort, reorganize, group, count, total or average data stored in a database

• Dashboard

  • monitors live and incoming data

  PROs

  • dynamic, automatic, and interactive
  • more stakeholder access
  • low maintenance

  CONs

  • labor-intensive design
  • can be leff efficient than reports
  • need to expect various errors
  • potentially unlceaned data