1. RTV3 Project Overview
2. Title: Real-Time Visibility 3   Dashboard
3. Key Objectives
   1. Additional Data: Inclusion of new columns that are meant to be visible and live in the database and BI tools.
   1. Optimization:  Improve reporting and analysis processes through addressing errors and introducing enhancements.
   1. KPI Harmonization: Ensure current dashboards and analytics remain precise as new data is incorporated.

2. Description

• Real-Time Visibility 3 is a project to add to the initial project of Real-Time Visibility 2. The aim was to integrate six new columns into the RTV 2 Global Table to improve data visibility and enhance business intelligence analysis. These columns are:
  • Payment Date 2
  • Payment Date 3
  • Start Date
  • Sub Days
  • Sub End
  • Sub Left

The Lagos office also rolled out new products, prompting the creation of two tables: Lagos 1 Cyber Security and Lagos 1 UI/UX. These tables were merged with the existing database to guarantee compatibility with reports and dashboards.

The project’s purpose was to ensure that the new data points are fully integrated within the ETL process and visible in all reports and dashboards, without disrupting existing KPI cards, charts, and slicers.

3.  Benefits to Business

The inclusion of these new columns brought about many gains, which include:

• Performance tracking improved through real-time criteria.
• New income streams from the extra opportunities.
• New course product handling for UI/UX and Cyber Security.
• Improved cash flow management through enhanced visibility of payment data.
• Bolstered community building through focused marketing strategies. Optimized email marketing with advanced data insights.

4. Implementation

• Difficulties in ETL Update
  • ETL refresh Errors due to strange columns. They were sorted according to the data cleaning steps.
  • Ensuring that new columns are accommodated by editing the parent table.
• New Date Table Introduction
  • To reduce duplication from nine different date columns, a centralized date table was implemented. This choice simplified the dataset and enhanced analytical performance by avoiding extra processing for date attributes like day name, month name, and weekday.
• Introduction of Progress Bar for Data Entry Tracking
  • A progress bar was introduced to monitor data entry for the new columns.
  • Timely data updates were guaranteed.
  • Progress targets were trackable, target setting and accountability were achievable by management.

5. Recommendations

• Data Refresh and Error Handling to be Automated.
  • Configure BI dashboards to refresh automatically on a schedule, minimizing human intervention.
  • ETL errors alert should be made to come automatically for immediate checks and fixing.
• Constant Improvement in Data Quality
  •   Date Column Data Validation Analysis Introduction: Perform routine audits of date fields (e.g., Payment Date 2, Payment Date 3, Start Date) to maintain accuracy and consistency. Wrong dates can compromise financial reports, distort revenue recognition, and hinder sound decision-making.
  • Define clear data entry standards and implement instant validation checks in the BI system to detect anomalies before submission.
  • Educate staff on proper data entry standards to ensure accuracy and consistency in new fields.
  • Implement documented protocols and best practices so the team can minimize discrepancies in new entries.
  • Provide organized training sessions for data entry staff to ensure consistency in newly added fields.

• Makes Dashboard Very Interactive
  • Refine dashboard filters to allow deeper insights into payment schedules and subscription trends.
• Enable drill-through functionality to provide a detailed analysis of revenue patterns and student participation

6. Outcome Perspectives

• Revenue Tracking Enhancement: Improved visibility into payment cycles allows the finance team to optimize collection strategies, enhancing cash flow administration.
• Quick Decision: Consolidated date tables and streamlined ETL workflows accelerate report creation, allowing leadership to respond quickly.
• Swift Accuracy of Data: Eliminating duplicate date columns and applying error-handling techniques results in clearer, more dependable insights.
• Synchronization of Sales & Marketing: Refined data segmentation enables personalized email campaigns, driving stronger engagement and improved conversion rates.
• Expandable Framework for Long-Term Success: Improved BI capabilities enable broader data integration, laying the groundwork for advanced reporting.

7. Conclusion

Through the Real-Time Visibility 3 project, earlier limitations were overcome, resulting in more reliable data and enabling deeper BI analysis. The expanded data model—featuring additional tables and columns—provides powerful resources for tracking results, managing finances, and guiding sustainable growth.

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Interactive Dashboard: Explore the interactive Power BI dashboard below to experience KPIs, filters, and visualizations in real time.