Project Deliverable: Data Visualization Suite - Research & Design Requirements

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1. Introduction & Project Overview

This document outlines the initial research and design requirements for the proposed Data Visualization Suite. The objective is to establish a robust foundation for a powerful, intuitive, and aesthetically pleasing platform that empowers users to transform complex data into actionable insights. This deliverable serves as a blueprint for the subsequent design and development phases, ensuring all stakeholders are aligned on the core vision and specifications.

Our aim is to create a suite that is not only highly functional but also provides an exceptional user experience, fostering data exploration and storytelling.

2. Detailed Design Specifications

The Data Visualization Suite will be engineered with a focus on flexibility, performance, and user empowerment.

2.1 Core Functionality Requirements:

• Interactive Dashboard Builder:

* Drag-and-drop interface for creating and arranging visualizations.

* Support for multiple dashboards within a single project/suite.

* Global and contextual filtering capabilities (date ranges, dimensions, measures).

* Cross-filtering interactions between charts on a dashboard.

* Drill-down capabilities for exploring data hierarchies.

* Layout options (grid, free-form, responsive).

• Comprehensive Chart Library:

* Standard Charts: Bar (vertical/horizontal), Line, Area, Pie/Donut, Scatter Plot, Bubble Chart.

* Advanced Charts: Heatmaps, Treemaps, Sunburst, Box & Whisker.

* Geospatial Visualizations: Choropleth maps, Point maps (requiring geo-data support).

* Table/Pivot Table views with sorting and aggregation.

* Key Performance Indicator (KPI) cards with trend indicators.

• Data Connectivity & Management:

* Support for various data sources: SQL databases (PostgreSQL, MySQL, SQL Server), NoSQL (MongoDB, Elasticsearch - via connectors), Cloud data warehouses (Snowflake, BigQuery, Redshift), APIs, Flat Files (CSV, Excel, JSON).

* Secure credential management for data sources.

* Data preview and schema discovery.

* Basic data transformation capabilities (e.g., column renaming, data type conversion, simple calculated fields).

• Customization & Theming:

* Ability to customize chart properties (colors, labels, axes, legends, tooltips).

* Pre-defined and custom themes for dashboards.

* Branding options (logo, primary colors).

• Collaboration & Sharing:

* Secure sharing of dashboards and reports with specific users or teams.

* Export options: PNG, JPEG, PDF, CSV, Excel.

* Embeddable dashboard links for external applications.

• User & Role Management:

* Authentication (SSO integration where applicable).

* Role-based access control (RBAC) for data sources, dashboards, and features.

• Real-time & Scheduled Updates:

* Option for real-time data refresh for specific data sources.

* Scheduled data refreshes for dashboards and reports.

• Responsiveness:

* Optimized viewing experience across desktop, tablet, and mobile devices.

2.2 Non-Functional Requirements:

• Performance: Fast loading times for dashboards and interactive visualizations, even with large datasets. Efficient query execution.
• Security: Robust data encryption (at rest and in transit), adherence to industry best practices for access control, vulnerability management.
• Scalability: Architecture designed to handle increasing data volumes, concurrent users, and growing number of dashboards.
• Reliability: High availability and fault tolerance.
• Maintainability: Clean, modular codebase for easy updates and feature additions.

3. Wireframe Descriptions (Conceptual)

The following describes the conceptual layout and key interactions for critical screens within the Data Visualization Suite. These descriptions will inform the detailed wireframe creation in the next phase.

3.1. Dashboard Overview Screen:

• Layout: Three-column layout.

* Left Sidebar (Persistent Navigation): Logo, Primary Navigation (Home, Dashboards, Data Sources, Reports, Users & Settings, Help).

* Header (Top Bar): Global Search, User Profile (Avatar, Logout), Notifications/Alerts, "Create New Dashboard" CTA.

* Main Content Area (Dashboard Cards): Grid-based display of "Dashboard Cards." Each card includes:

* Dashboard Title & Description.

* Thumbnail preview of the dashboard.

* Key metrics (e.g., # of views, last updated).

* Action menu (Edit, Share, Duplicate, Delete, View).

* Filter/Sort Panel (Collapsible Right Sidebar): Options to filter dashboards by owner, tags, last modified date, and sort by name, creation date, etc.

3.2. Individual Dashboard View Screen:

• Layout: Header, Optional Left/Right Filter Panels, Main Visualization Canvas.

* Header: Dashboard Title, "Last Updated" timestamp, "Edit/View" Toggle, "Share" button, "Export" button, "Refresh" button.

* Global Filter Bar (Top of Canvas, Collapsible): Date range picker, dropdowns for key global dimensions (e.g., Region, Product Category).

* Main Visualization Canvas: A dynamic grid or free-form layout where individual charts and KPI cards are arranged.

* Each visualization widget has: Title, optional Legend, interactive elements (tooltips, click-to-filter, zoom).

* Contextual menu (three dots) on each widget for "Edit Chart," "Duplicate," "Export Data," "Remove."

* Interaction: Clicking on a data point in one chart can filter data in other related charts (cross-filtering). Hovering shows detailed tooltips.

3.3. Data Source Configuration Screen:

• Layout: Left Sidebar for Data Source List, Right Main Area for Configuration.

* Left Sidebar: List of existing data sources. "Add New Data Source" CTA. Each list item shows source name, type, and connection status.

* Main Content Area (Wizard-like Flow for New Source):

* Step 1: Select Data Source Type: Icons/list of supported databases, APIs, file types.

* Step 2: Connection Details: Input fields for host, port, username, password, database name, API keys, file upload.

* Step 3: Data Preview & Schema Selection: Display of tables/collections available, ability to select specific tables/fields, basic data type inference, option to create custom queries/views.

* Step 4: Naming & Description: Assign a name and description to the data source.

* "Test Connection" and "Save" buttons.

3.4. Chart Builder/Editor Screen:

• Layout: Three-panel layout: Data Fields, Chart Canvas, Properties Panel.

* Left Panel (Data Fields): Tree view of connected data source fields, categorized into Dimensions (categorical) and Measures (numerical). Search bar for fields.

* Middle Panel (Chart Canvas):

* Drag-and-drop zones for X-axis, Y-axis, Color, Size, Filters, Tooltips.

* "Chart Type" selector (dropdown/icons).

* Live preview of the chart as fields are added/modified.

* Right Panel (Properties Panel):

* General: Chart Title, Description.

* Data: Aggregation methods, sorting, filtering specific to this chart.

* Axes: Axis labels, min/max values, tick format.

* Colors: Color palette selector, conditional formatting.

* Labels: Data labels, tooltips customization.

* Interaction: Enable/disable drill-down, cross-filtering.

* "Save Chart" and "Cancel" buttons.

4. Color Palettes

A cohesive and accessible color palette is crucial for both UI aesthetics and effective data communication.

4.1. Primary UI Palette:

These colors define the overall look and feel of the application interface.

• Primary Brand Blue (Action/Highlight): #3498DB (Used for CTAs, active states, primary navigation highlights)
• Dark Navy (Primary Background/Text): #2C3E50 (Used for headers, main text, prominent UI elements)
• Light Gray (Secondary Background/Cards): #ECF0F1 (Used for card backgrounds, secondary containers, subtle separators)
• Medium Gray (Borders/Dividers): #BDC3C7 (Used for borders, dividers, disabled states)
• White (Text/Icons): #FFFFFF (Used for text on dark backgrounds, icons)
• Dark Gray (Secondary Text): #7F8C8D (Used for helper text, less prominent information)

4.2. Data Visualization Palette (Categorical):

A carefully selected set of distinct and harmonious colors for representing different categories in charts. Ensures good contrast and differentiation.

• #3498DB (Blue)
• #2ECC71 (Emerald Green)
• #E67E22 (Carrot Orange)
• #9B59B6 (Amethyst Purple)
• #E74C3C (Alizarin Red)
• #1ABC9C (Turquoise)
• #F1C40F (Sunflower Yellow)
• #34495E (Wet Asphalt - Dark Grey)
• #95A5A6 (Concrete - Light Grey)
• #C0392B (Pomegranate - Dark Red)

Note: For sequential or diverging data, gradient scales will be dynamically generated based on a selected base color.

4.3. Semantic Colors:

Used to convey specific states and feedback to the user.

• Success: #2ECC71 (Green - e.g., "Data connected successfully")
• Warning: #F1C40F (Yellow - e.g., "Connection unstable")
• Error: #E74C3C (Red - e.g., "Failed to load data")
• Info: #3498DB (Blue - e.g., "New update available")

4.4. Accessibility Considerations:

• All color combinations will adhere to WCAG 2.1 AA contrast standards for text and interactive elements.
• The data visualization palette is designed to be perceptually distinct, even for users with common forms of color blindness. Patterns or textures will be used as a secondary encoding for critical data points where color alone might be insufficient.

5. User Experience (UX) Recommendations

Delivering a superior user experience is paramount for a data visualization suite.

• Clarity and Simplicity:

* Minimize visual clutter; focus on the data.

* Intuitive navigation and clear labeling for all UI elements.

* Progressive disclosure: show only what's necessary at each step, reveal more detail on demand.

• Consistency:

* Maintain consistent UI patterns, terminology, and interaction models across the entire application.

* Predictable behavior for common actions (e.g., filtering, editing).

• Interactivity & Direct Manipulation:

* Enable direct interaction with charts (e.g., clicking segments, brushing to select ranges, zooming/panning).

* Instant feedback for user actions (e.g., filter application, data refresh).

* Rich tooltips that provide detailed information on hover without obscuring the view.

• Feedback & Guidance:

* Provide clear system feedback for loading states, errors, success messages, and warnings.

* Onboarding tours and contextual help for new features or complex workflows.

* Informative empty states for dashboards or data sources.

• Accessibility:

* Ensure keyboard navigation support for all interactive elements.

* High-contrast options and

This document outlines the detailed design specifications for the "Data Visualization Suite," focusing on a professional, intuitive, and highly functional user experience. These specifications will guide the visual design, interaction patterns, and overall user journey, ensuring a robust and engaging platform for data exploration and insight generation.

1. Design Specifications

The Data Visualization Suite will adhere to a modern, clean, and minimalist design aesthetic, prioritizing data clarity and user efficiency.

1.1. Overall Structure & Layout

• Dashboard-Centric: The primary user experience will revolve around customizable dashboards that serve as the main entry point for data insights.
• Persistent Global Navigation: A left-hand sidebar or top-bar navigation will provide quick access to key modules (Dashboards, Reports, Data Sources, Settings, Help).
• Responsive Design: The suite will be fully responsive, ensuring optimal viewing and interaction across various devices (desktop, tablet, mobile) with graceful degradation for smaller screens.
• Modular Components: All visualizations and UI elements will be modular, allowing for drag-and-drop customization, resizing, and reordering within dashboard layouts.
• Scalable Architecture: The design will accommodate a growing number of data sources, reports, and users without compromising performance or usability.

1.2. Key UI Components & Interactions

• Global Header:

* Logo: Prominently displayed.

* Search Bar: Global search for dashboards, reports, and data fields.

* User Profile: Access to user settings, profile management, and logout.

* Notifications: Icon for system alerts, report updates, or shared content.

• Left Navigation (Sidebar):

* Collapsible/Expandable to maximize content area.

* Icons with text labels for primary navigation items.

* Active state clearly indicated.

• Dashboard Canvas:

* Grid-Based Layout: Flexible grid system (e.g., 12-column) for precise placement and resizing of widgets.

* Drag-and-Drop: Intuitive interaction for rearranging visualizations.

* Global Filters: Date range picker, dropdowns, multi-select filters applicable to the entire dashboard.

* Dashboard Actions: Save, Share, Export (PDF, CSV, PNG), Edit Layout.

• Visualization Widgets/Cards:

* Each visualization will reside within a card-like container.

* Header: Chart title, last updated timestamp.

* Context Menu (Ellipsis icon): Options for drill-down, view data, export chart, duplicate, remove.

* Interactive Elements: Tooltips on hover, click-to-filter/drill-down, zoom/pan functionality where applicable.

* Loading States: Clear indicators for data loading or refresh.

• Data Table View:

* Interactive tables with sorting, pagination, and column filtering.

* Export to CSV/Excel functionality.

• Forms & Modals:

* Clean, well-aligned input fields, checkboxes, radio buttons, and dropdowns.

* Clear validation messages.

* Accessible design for all form elements.

1.3. Typography

• Primary Font: A sans-serif font (e.g., Inter, Open Sans, Lato) for readability and modern aesthetic.

* Headings (H1-H6): Used for dashboard titles, section headers, and chart titles. Varied weights and sizes for hierarchy.

* Body Text: Used for descriptions, labels, and general content.

* Monospace Font: Optional for code snippets or specific data representations.

• Font Sizes: Scaled appropriately for responsiveness and accessibility (e.g., 14px base body text).
• Line Height & Letter Spacing: Optimized for readability.

2. Wireframe Descriptions

The following descriptions outline the key views and their functional elements.

2.1. Dashboard Overview / Home Screen

• Purpose: Provide users with a centralized view of their most important data, quick access to frequently used dashboards, and a starting point for exploration.
• Key Elements:

* Global Header: (Logo, Search, User Profile, Notifications).

* Left Navigation: (Dashboards, Reports, Data Sources, Settings, Help).

* Main Content Area:

* "My Dashboards" Section: Grid or list view of user's created/saved dashboards with thumbnails, titles, and last modified dates.

* "Shared Dashboards" Section: Similar view for dashboards shared by others.

* "Explore Data" / "Create New Dashboard" CTA: Prominently displayed button to initiate new data exploration or dashboard creation.

* "Recent Activity" (Optional): List of recently viewed dashboards/reports.

* Empty State: Clear instructions and a CTA for new users to get started.

2.2. Individual Dashboard View

• Purpose: Display a specific dashboard with its collection of visualizations, filters, and interactive elements.
• Key Elements:

* Global Header & Left Navigation: (As above).

* Dashboard Header:

* Dashboard Title: Editable.

* Description (Optional): Short context.

* Last Updated: Timestamp.

* Actions: "Edit Layout," "Share," "Export" (PDF, CSV, PNG), "Refresh Data."

* Global Filter Bar:

* Date Range Picker: Predefined ranges (e.g., Last 7 Days, This Month) and custom range selection.

* Dropdown Filters: For key dimensions (e.g., Region, Product Category, Segment). Multi-select enabled.

* Apply/Reset Filters Button.

* Visualization Grid:

* Multiple Visualization Cards: Arranged in a flexible grid. Each card includes:

* Chart Title.

* Visualization (Bar chart, Line chart, Pie chart, Scatter plot, Map, Gauge, Table, etc.).

* Hover Tooltips for data points.

* Context Menu (Ellipsis icon) for specific chart actions (e.g., "View Underlying Data," "Export Chart Image," "Add to Report").

* Loading spinner on data refresh.

* Drag Handle: For rearranging cards in edit mode.

* Resize Handles: For adjusting card dimensions in edit mode.

2.3. Report Builder / Editor View

• Purpose: Allow users to create, configure, and manage scheduled reports based on dashboard content or custom queries.
• Key Elements:

* Global Header & Left Navigation: (As above).

* Report Name & Description Input Fields.

* Report Content Selection:

* "Add from Dashboard": Select existing visualizations from a chosen dashboard.

* "Add Custom Chart": Link to a simplified chart builder interface.

* "Add Text Block": For static text or executive summaries.

* Content Preview Area: Real-time preview of the report layout.

* Scheduling Options:

* Frequency: Daily, Weekly, Monthly, Custom.

* Time: Specific time of day.

* Recipients: Email addresses, user groups.

* Format: PDF, CSV, PNG.

* Actions: "Save," "Send Now," "Cancel."

2.4. Data Source Management View

• Purpose: Enable users to connect, configure, and manage various data sources.
• Key Elements:

* Global Header & Left Navigation: (As above).

* List of Connected Data Sources:

* Table/Card view showing Source Name, Type (e.g., SQL Database, Google Analytics, Salesforce), Status (Connected/Disconnected), Last Refreshed.

* Actions: "Edit," "Refresh," "Disconnect."

* "Add New Data Source" Button:

* Triggers a modal or new view for connection setup.

* Source Type Selection: List of supported connectors.

* Connection Details Form: (e.g., Host, Port, Database, Username, Password for SQL; API Key/OAuth for cloud services).

* Test Connection Button.

* Save/Cancel Buttons.

3. Color Palettes

The color palettes are designed for professionalism, readability, and effective data differentiation, with strong consideration for accessibility.

3.1. Primary UI Palette

This palette defines the core colors for the application's interface.

• Primary Blue (Brand Accent): #2196F3 (A vibrant, trustworthy blue for primary actions, active states, and branding.)
• Dark Gray (Primary Text/Navigation): #333333 (High contrast for readability.)
• Medium Gray (Secondary Text/Icons): #666666 (For less critical information, subtle icons.)
• Light Gray (Borders/Dividers): #E0E0E0 (Subtle separation of elements.)
• Background White: #FFFFFF (Clean, spacious canvas for dashboards.)
• Off-White/Lightest Gray (Hover/Alt Background): #F8F8F8 (For subtle hover states or alternating table rows.)

3.2. Data Visualization Palette

This palette is specifically curated for charts and graphs, ensuring distinctiveness and clarity. It will include categorical, sequential, and diverging options.

• Categorical Palette (Example): A set of 6-8 distinct, colorblind-friendly colors.

* #4CAF50 (Green)

* #FF9800 (Orange)

* #9C27B0 (Purple)

* #00BCD4 (Cyan)

* #F44336 (Red)

* #795548 (Brown)

(Additional colors will be selected to maintain distinctiveness for larger datasets)*

• Sequential Palette (Example - for gradients/heatmaps):

* Light Blue: #E3F2FD

* Medium Blue: #90CAF9

* Dark Blue: #2196F3

* Darker Blue: #1976D2

• Diverging Palette (Example - for positive/negative values):

* Red (Negative): #EF9A9A -> #D32F2F

* Neutral (Midpoint): #F5F5F5

* Green (Positive): #A5D6A7 -> #388E3C

• Accent & Highlight Colors:

* Success: #4CAF50 (Green)

* Warning: #FFC107 (Amber)

* Error: #F44336 (Red)

* Information: #2196F3 (Primary Blue)

3.3. Accessibility Considerations

• All color combinations will meet WCAG 2.1 AA standards for contrast ratio, ensuring readability for users with visual impairments.
• The data visualization palette will be tested for colorblind-friendliness using tools like Color Oracle or similar simulators.
• Information will not be conveyed solely through color; text labels, patterns, or icons will provide redundant coding where necessary.

4. UX Recommendations

These recommendations focus on enhancing the user experience through intuitive interactions, clear communication, and efficient workflows.

4.1. Clarity & Simplicity

• Progressive Disclosure: Present only essential information initially, revealing more complex details (e.g., chart configuration options) only when needed or requested.
• Minimalist Interface: Reduce visual clutter to allow data to be the focal point. Use whitespace effectively.
• Clear Labeling: All interactive elements, charts, and data points should have clear, concise labels. Avoid jargon where possible.
• Consistent Terminology: Use the same terms for the same concepts throughout the suite (e.g., always "Dashboard," never "Panel").

4.2. Consistency & Predictability

• Standard UI Patterns: Employ common design patterns for navigation, filtering, and data display to leverage users' existing mental models.
• Uniform Interaction: Similar elements should behave consistently (e.g., all clickable chart elements should highlight on hover).
• Visual Hierarchy: Use size, color, and placement to guide the user's eye and indicate importance.

4.3. Feedback & Responsiveness

• Loading States: Provide clear visual feedback (spinners, skeleton screens) during data loading or processing to manage user expectations.
• Action Confirmation: Confirm successful actions (e.g., "Dashboard Saved," "Report Sent") and provide clear error messages for

This document outlines the finalized design assets for your Data Visualization Suite, providing a comprehensive guide for its visual and interactive implementation. This deliverable serves as the blueprint for development, ensuring a consistent, intuitive, and high-performance user experience.

1. Executive Summary & Design Principles

This deliverable provides detailed design specifications, wireframe descriptions for key views, a comprehensive color palette, and critical User Experience (UX) recommendations. The design aims to deliver a powerful, user-friendly, and visually appealing suite that transforms complex data into actionable insights.

Core Design Principles:

• Clarity & Readability: Data must be easily digestible at a glance, with clear typography, intuitive layouts, and minimal visual clutter.
• Consistency: A unified design language across all components, ensuring a predictable and comfortable user journey.
• Interactivity & Empowerment: Users should be able to explore data dynamically, drill down into details, and customize their views effortlessly.
• Scalability & Flexibility: The design accommodates growth in data volume, visualization types, and user features, while remaining adaptable to various screen sizes.
• Accessibility: Designed with WCAG 2.1 AA guidelines in mind to ensure usability for a broad audience.
• Performance-Oriented: Visuals and interactions are optimized for rapid loading and smooth operation, even with large datasets.

2. Detailed Design Specifications

2.1. Dashboard & Layout System

• Grid System: Responsive 12-column grid (Bootstrap-like) for flexible widget placement.

* Breakpoints:

* xs: <576px (Mobile)

* sm: 576px - 767px (Tablet Portrait)

* md: 768px - 991px (Tablet Landscape)

* lg: 992px - 1199px (Desktop)

* xl: >1200px (Large Desktop)

* Gutters: 24px between columns, 24px vertical spacing between widgets.

• Modular Widgets: Each visualization (chart, KPI, table) is contained within a distinct card/widget.

* Widget Header: Title (H3/H4), ... (kebab) menu for options (Export, Refresh, Edit, Delete), Collapse/Expand icon.

* Widget Body: Contains the primary visualization.

* Resizing & Drag-and-Drop: Widgets should be draggable to rearrange and resizable (via corner handles) within the grid.

• Header Bar (Global):

* Left: Suite Logo, Suite Name (Data Visualization Suite - H2).

* Center: Global Date Range Selector (Dropdown with presets like "Last 7 Days," "This Month," "Custom Range").

* Right: Global Filters (e.g., Region, Department - accessible via a collapsible panel or modal), Search Icon, Notification Bell Icon, User Avatar/Menu (Profile, Settings, Logout).

• Sidebar Navigation (Left):

* Collapsed State: Icons only, on hover expands to show labels.

* Expanded State: Icons + Text Labels.

* Sections: Dashboards, Reports, Data Sources, Settings, Help.

* Active State: Highlighted background and/or accent color for the current page.

2.2. Chart & Graph Components

• Standard Chart Types: Bar Chart (vertical/horizontal), Line Chart, Area Chart, Pie/Donut Chart, Scatter Plot, Heatmap, Treemap, Gauge Chart, KPI Cards.
• Interactivity:

* Hover States: Display precise data points in a tooltip.

* Click-to-Filter: Clicking on a data segment (e.g., a bar, pie slice) should filter other related visualizations on the dashboard.

* Drill-down: Clicking on a data point can navigate to a more detailed view or expand a hierarchy.

* Zoom/Pan: For line/scatter plots, allow users to zoom into specific timeframes or data ranges.

• Labeling & Annotations:

* Titles: Clear, concise titles for each chart (H4/H5).

* Axes: Clearly labeled X and Y axes with appropriate units.

* Legends: Positioned strategically (top, bottom, right) with toggle functionality to show/hide data series.

* Data Labels: Toggleable option to display values directly on chart elements.

* Tooltips: Rich tooltips displaying all relevant data points on hover.

• Styling:

* Borders: Subtle 1px border (#dee2e6) for chart containers.

* Backgrounds: White (#ffffff) for chart areas.

* Gridlines: Light grey (#e9ecef) for both X and Y axes, dashed or solid.

* Animations: Smooth, subtle transitions for data updates and interactions.

2.3. Filtering & Interaction Elements

• Dropdowns (Single/Multi-select):

* Clear labels, search functionality within dropdowns for long lists.

* Visual indicators for selected items.

• Sliders: For numeric ranges or continuous values. Clear min/max labels and current range display.
• Date Pickers: Calendar-based selection for single dates, date ranges. Presets (e.g., "Today," "Last Month," "YTD").
• Search Bars: With clear placeholder text and a search icon.
• Buttons:

* Primary: Solid background, white text. For main actions (e.g., "Apply Filters," "Save Dashboard").

* Secondary: Outline, primary text. For less critical actions (e.g., "Clear Filters," "Cancel").

* Tertiary/Ghost: Text only. For subtle actions (e.g., "View Details").

* States: Default, Hover, Active, Disabled.

2.4. Table & Data Grid Components

• Structure: Clean, tabular display of raw or aggregated data.
• Features:

* Pagination: Customizable rows per page.

* Sorting: Clickable column headers for ascending/descending sort.

* Column Resizing/Reordering: User-configurable.

* Search/Filter per Column: Optional input fields or dropdowns within column headers.

* Row Highlighting: On hover.

* Export Options: CSV, XLSX, PDF.

• Styling: Zebra striping for readability (lightest grey background). Fixed header on scroll.

2.5. Typography

• Font Family: Inter (Primary, Sans-serif) - chosen for its readability, modern aesthetic, and versatility across various screen sizes. Fallback: Arial, sans-serif.
• Font Weights: Regular (400), Medium (500), Semi-Bold (600), Bold (700).
• Font Sizes & Usage:

* H1: 36px (Suite Title)

* H2: 28px (Section Titles)

* H3: 22px (Dashboard Titles)

* H4: 18px (Widget Titles)

* H5: 16px (Sub-headings, Chart Titles)

* Body Text: 14px - 16px (Primary content)

* Labels/Captions: 12px - 13px (Chart labels, metadata)

* Buttons: 14px (Consistent with body text)

• Line Height: 1.5 for body text, 1.2 for headings.
• Letter Spacing: Default (normal) for body, slightly tighter for headings (-0.02em).

2.6. Iconography

• Library: Material Design Icons (filled style) or Font Awesome Pro (solid style) for consistency.
• Style: Consistent outline or filled style throughout the application.
• Usage:

* Navigation elements (Dashboards, Settings).

* Actionable items (Export, Refresh, Edit, Delete, Filter).

* Status indicators (Success, Warning, Error).