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Types of Analytical Applications

Visualization

Foundation

STRATEGIC

  • Goals
    • Provides a big-picture view of KPIs tied to long-term goals.
    • Track strategic performance & business health.
  • Target Users - Decision makers & Senior Management.
  • Analysis type
    • High level measures of performance, Snapshots of monthly and quarterly data.
    • Long-term and strategic
    • Update Frequency: Update daily to weekly
    • Data Granularity: Aggregated KPIs
    • Interactivity Level: Low to medium (summaries, filters)
  • Key Design Considerations
    • Displays a high level overview of the business state
    • Focuses on high-level performance measures and Key KPIs
    • More focus on actual goals instead of target
    • Typically displays static snapshots of daily, weekly, or monthly data
    • Provides limited user interaction
    • Showcases opportunities available to the business
  • Best Practices
    • Avoid including too many details
    • Avoid use of advance visualizations
    • Highlight outliers effectively
    • Use thresholds, highlight positive and negative values
    • Focus on actionable insights rather than making the dashboard attractive
    • Strategic progress, high-level KPIs
  • How?
    • Highlight KPIs
    • Show trends with line or area charts
    • Include comparisons

TACTICAL

  • Goals - Tracks progress on short to mid-term goals for specific teams or projects.
  • Target Users - For team leaders, department heads, and middle management.
  • Analysis type - manage department goals or track project results.
  • How?
    • Use department-specific KPIs
    • Enable drill-downs, and incorporate visuals like bullet charts and bar charts to measure progress effectively.

ANALYTICAL

  • Goals
    • Lets users explore data deeply to find patterns, trends, and actionable insights.
    • Explore trends, identify patterns, root cause analysis.
  • Target Users - Mid management & Planning team.
  • Analysis type
    • Complex data with rich comparison. Interactive display and historical data.
    • Mid-term, data-informed
    • Weekly to years of historical data
    • Update Frequency: On-demand or periodic
    • Data Granularity: Granular, detailed data with drill-down capabilities
    • Interactivity Level: High (filters, segments, slicers, custom queries)
  • Key Design Considerations
    • More complex data with rich comparisons
    • More focus on historic data
    • Interactive display with high user interaction
    • Typically displays historic data with YOY (Year on Year) comparison
    • Showcases an in depth analysis of data
    • Includes drill down functionalities
    • Offers the flexibility to filter data from multiple parameters
    • Includes data discovery capabilities
  • Best Practices
    • Includes data discovery capabilities
    • Highlight insights properly
    • Focus on actionable insights rather than making the dashboard attractive
    • Why things happened, what may happen
  • How?
    • Incorporate interactive charts with drill- down options
    • Compare historical data for analysis
    • Use visuals like scatter plots and tables to uncover patterns.

OPERATIONAL

  • Goals
    • Monitors daily activities in real-time to ensure smooth operations.
    • Monitor operations & trigger fast actions.
  • Target Users - Operational workers.
  • Analysis type
    • Monitoring activities that are constantly changing. Shows real time or near real time data.
    • Immediate, tactical
    • Real-time to daily
    • Update Frequency: Real-time or near-real-time
    • Data Granularity: Real-time metrics, individual transactions
    • Interactivity Level: Very high (live updates, alerts, quick filters)
  • Key Design Considerations
    • Focuses on high level measures of performance and Key KPIs
    • More focus on real or near real time data
    • Quick & static snapshot
    • Typically display static snapshots of daily data
    • Displays high -level overview of the state of the business
    • Showcases up and down in daily business
    • More focus on outliers
  • Best Practices
    • Avoid putting too many details
    • Keep visualizations simple but actionable
    • Make good use of per-attentive attributes
    • Use thresholds and highlight positive & negative values
    • Focus on actionable insights rather than making the dashboard attractive
    • What’s happening now, what action is needed
  • How?
    • Focus on real-time metrics
    • Include alerts for quick action
    • Use visuals like gauges, progress bars, and heatmaps to track performance efficiently.