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June 20, 2024

Power BI dashboard For Finance / Banking Using CoPilot

Use Case: Finance Dashboard for Auditing in the Banking Industry

Objective: Develop a comprehensive Finance Dashboard to streamline and enhance the auditing process in a banking institution using Microsoft Power BI and Copilot.

 Jasa Azure Data Factory

 Jasa Azure Synapse

 Jasa Azure Data Lake

 Jasa Power Bi

 Jasa Microsoft Copilot

 Jasa Microsoft Purview

 Jasa Dashboard Power BI

 Jasa Data Lake Microsoft

Jakarta Indonesia

Solution Overview

  1. Data Integration and Preparation:
  2. Data Modeling and Management:
  3. Analytics and Reporting:
  4. AI and Automation:
  5. Security and Compliance:

Detailed Solutions and Services

1. Data Integration and Preparation

  • Azure Data Factory (ADF):
  • Azure Synapse Analytics:
  • Azure Data Lake Storage (ADLS):

2. Data Modeling and Management

  • Power BI Dataflows:
  • Dataverse:

3. Analytics and Reporting

  • Power BI Service:
  • Power BI Desktop:
  • Power BI Embedded:

4. AI and Automation

  • Copilot in Power BI:
  • Azure Cognitive Services:

5. Security and Compliance

  • Azure Active Directory (AAD):
  • Microsoft Purview:
  • Azure Security Center:

Implementation Plan

  1. Assessment and Planning:
  2. Data Integration Setup:
  3. Data Modeling:
  4. Dashboard Development:
  5. Security and Compliance Configuration:
  6. Deployment and Training:
  7. Monitoring and Optimization:

Benefits

  • Enhanced Efficiency: Automates data preparation and report generation, reducing manual effort.
  • Improved Accuracy: Ensures data consistency and reliability through centralized data management.
  • Better Insights: Utilizes AI to provide actionable insights and detect anomalies.
  • Regulatory Compliance: Maintains compliance with industry regulations through robust data governance.
  • User-Friendly: Empowers auditors with intuitive tools for data analysis and reporting.

By leveraging Microsoft Power BI and Copilot, the banking industry can significantly improve the efficiency and effectiveness of its auditing processes, ensuring timely and accurate financial reporting.

Summary of Problems Solved and Benefits

Problems Solved:

  • Manual data integration and preparation
  • Inefficient and slow data querying
  • Data silos and inconsistent data
  • Complexity in data modeling and report creation
  • Difficulty in sharing reports and collaboration
  • Security risks and uncontrolled access
  • Compliance issues with industry regulations
  • Limited advanced analytics capabilities

Benefits:

  • Enhanced efficiency and reduced manual effort
  • High-performance data analytics
  • Centralized, secure data storage
  • Streamlined data transformation processes
  • Unified data management
  • Easy sharing and collaboration on reports and dashboards
  • Advanced reporting capabilities
  • Embedded analytics in banking applications
  • Automated insights and report generation
  • Enhanced AI capabilities for fraud detection and predictive analytics
  • Secure, role-based access management
  • Robust data governance ensuring compliance with regulations
  • Comprehensive security management
  • Improved performance and user satisfaction through continuous monitoring and optimization