Advanced Risk Analysis Dashboard

Introduction

This notebook provides comprehensive risk analysis tools for project management, including:

• Risk Matrix Visualization
• Temporal Analysis
• Category Distribution
• Mitigation Effectiveness
• Resource Allocation Analysis
• Predictive Analytics

Setup and Data Loading

# Initialize required modules and libraries
alias Resolvinator.Notebooks.Setup
setup = Setup.setup()
import Explorer.DataFrame
alias Explorer.Series
alias Resolvinator.{Repo, Risks, Resources}
alias Resolvinator.Analytics.RiskAnalyzer

# Setup visualization tools
Kino.VegaLite.setup()

# Create interactive inputs for analysis parameters
date_range = Kino.Input.date_range("Date Range")
category_select = Kino.Input.select("Risk Category", ["All" | Risks.list_categories()])
impact_threshold = Kino.Input.number("Impact Threshold", default: 5)

Data Preparation and Validation

# Fetch and validate risk data
risks_with_associations =
  try do
    Risks.list_risks(includes: [:mitigations, :impacts, :requirements])
    |> Enum.map(fn risk ->
      %{
        id: risk.id,
        name: risk.name,
        category: risk.category,
        probability: risk.probability,
        impact: risk.impact,
        status: risk.status,
        description: risk.description,
        mitigation_count: length(risk.mitigations),
        total_impact_score: Enum.sum(Enum.map(risk.impacts, & &1.score)),
        resource_requirements: length(risk.requirements),
        created_at: risk.inserted_at,
        updated_at: risk.updated_at,
        days_open: Date.diff(Date.utc_today(), Date.from_iso8601!(risk.inserted_at))
      }
    end)
    |> DataFrame.new()
  rescue
    e in RuntimeError -> 
      IO.puts("Error loading risk data: #{inspect(e)}")
      DataFrame.new([])
  end

# Display interactive data table with filtering
Kino.DataTable.new(risks_with_associations, keys: [:id, :name, :category])