Data analytics

BI - BU intelligence BA - BU analytics both Analytics sec-monitoring-track - logs-metrics-traces nData

• what? BI, BA, everything related to data - the umbrella term

  • Includes all type of biz data
  • like Accounting but for any data

• 0

  • Data modeling
  • data warehouses
  • ETL - Extract, Transform, Load: clean & prepare data
  • Data Prep
    • Wrangling - cleaning/reshaping raw data to usable format
      • used in initial phases
      • doesn’t change the data itself often
      • e.g.
        • Cleaning (e.g. missing values, duplicates)
        • Structuring (e.g. flattening nested data)
        • Enrichment (e.g. joining datasets)
        • Validation
    • Transformation - change data to solve specific problem/goal
      • used after wrangling
      • e.g.
        • Converting currencies
        • Aggregating daily sales into monthly totals
        • Encoding categorical variables for ML
  • Types of biz data
    • descriptive - What happened?
      • Summarizes historical data to identify patterns & trends.
    • Diagnostic - What was the error?
      • find the root causes of events or behaviors.
    • Predictive - What will happen?
      • statistical models and machine learning to forecast future outcomes.
    • prescriptive - What should we do? why of things
      • Recommends actions based on data, predictions, and optimization models.
  • Roles
    • Main 3
      • Data engineer Data analytics
        • anything that happens before data gets to db
        • Extract, validate, ETL data
        • Builds pipeline/infra needed for the other 2 to work
      • Data analyst BI - BU intelligence
      • Data scientist BA - BU analytics