Unified Data Reporting System Development

May you kindly assist us in creating an automated system to gather data from multiple sources, including Manage Engine, Fresh Desk ticketing system, antivirus reports, and 0365 (Office 365) emails, and present it in a unified report for clients. Final Technical Document Requirements System Overview: - Purpose: Consolidate data from various sources (ManageEngine RMM, Freshdesk, Bitdefender, Office 365) into a unified report. - Data Sources: - ManageEngine RMM: CPU usage, RAM performance, disk space usage, network performance. - Freshdesk: Total tickets per client domain name per month, ticket volume, resolution time. - Bitdefender: Expiry/renewal date, license installation date, license status, security events, performance impact. - Office 365: OneDrive space usage, email volume, email total size, spam rate. - Reporting: - Generate comprehensive reports with key performance indicators (KPIs) and visualizations. - Provide flexibility for customization of reports. Data Extraction and Transformation - API Integration: Utilize APIs provided by the data sources whenever possible. - Data Extraction Methods: Employ appropriate data extraction techniques (e.g., web scraping, database queries) for sources without APIs. - Data Cleaning and Transformation: - Standardize data formats. - Handle missing values. - Transform data into a suitable structure for reporting. - Data Enrichment: - Calculate derived metrics (e.g., average resolution time, spam rate). - Analyze correlations between different metrics. Data Storage - Centralized Data Warehouse: Implement a centralized data warehouse (e.g., SQL Server, PostgreSQL) to store extracted data. - Data Security: Ensure data security measures, including encryption and access controls. Reporting and Visualization - Business Intelligence Tool: Use a powerful business intelligence tool (e.g., Power BI) for reporting and visualization. - Custom Dashboards: Create customizable dashboards to present key metrics and trends. - Visualization Types: Utilize various visualization types (e.g., charts, graphs) to effectively communicate data. - KPIs: Define and calculate relevant KPIs to measure system performance and identify trends. Automation - Scheduled Data Refresh: Automate the process of data extraction, transformation, and loading into the data warehouse. - Report Generation: Automatically generate reports based on predefined templates and distribution lists. Security and Privacy - Data Encryption: Implement data encryption measures to protect sensitive information. - Access Controls: Restrict access to data and reports based on user roles and permissions. - Compliance: Ensure compliance with relevant data privacy regulations. System Architecture - Diagram: Provide a high-level system architecture diagram illustrating the flow of data and processes. Technical Specifications - Hardware Requirements: Specify hardware requirements (e.g., server specifications, storage capacity). - Software Requirements: List necessary software components (e.g., operating system, database, business intelligence tool). - API Usage: Detail the APIs to be utilized from each data source. - Data Extraction Methods: Describe the methods to be used for extracting data from sources without APIs. Deployment and Maintenance - Deployment Plan: Outline the deployment process and timeline. - Maintenance Plan: Define maintenance procedures, including backups, updates, and troubleshooting. User Interface and Accessibility - User Interface Design: Specify the desired user interface design and features. - Accessibility: Ensure the system is accessible to users with disabilities. Testing and Quality Assurance - Test Plan: Develop a comprehensive test plan to validate system functionality and performance. - Quality Assurance Standards: Adhere to quality assurance standards and best practices. By following these technical requirements, you can effectively develop an automated system to gather and report data from multiple sources, providing valuable insights for your organization. Enhanced Reporting Requirements: Executive Summary Report Executive Summary Report - Purpose: Provide a concise overview of key findings and insights from the data. - Key Metrics: Highlight the most important metrics and their trends. - Executive-Friendly Language: Use clear and concise language that is easily understandable by non-technical executives. - Visualizations: Incorporate visually appealing and informative graphs to support key points. Graph Recommendations - Line Graphs: For showing trends over time (e.g., ticket volume, spam rate, CPU usage). - Bar Graphs: For comparing values across different categories (e.g., ticket volume by client domain, disk space usage by directory). - Pie Charts: For representing proportions or percentages (e.g., distribution of ticket types, spam rate). - Heatmaps: For visualizing relationships between two variables (e.g., correlation between CPU usage and RAM usage). - Interactive Dashboards: Allow executives to explore data and drill down into specific areas of interest. Example Executive Summary Report Topics - Overall System Health: - Key performance indicators (KPIs) for system health (e.g., average CPU usage, disk space utilization). - Trends in system performance over time. - Security Posture: - Number and types of security threats detected. - Effectiveness of security measures. - Trends in security incidents. - Ticket Management Efficiency: - Average resolution time for tickets. - Ticket volume by category or priority. - Customer satisfaction metrics. - Office 365 Usage: - OneDrive storage usage trends. - Email volume and size analysis. - Spam rate and filtering effectiveness. Additional Considerations - Customization: Allow executives to customize the executive summary report to focus on specific areas of interest. - Data Storytelling: Use the report to tell a compelling story about the data, highlighting key findings and insights.